ALBERT

Description: ABSTRACT The present study investigates the characteristics of active and break cycles associated with the Indian summer monsoon (ISM) during developing and decaying phase of El Niño and in the years in which Indian Ocean Dipole (IOD) co-occurred with El Niño (co-occurred years). Observations show that break days are more in number (∼2–3 times) and long lasting (∼15–20 days) than active days in El Niño developing summers and vice versa for decay years. During El Niño developing years, northward propagation is well organized with significant anomalies in both active and break phases. The increased convection associated with active phase persists longer over Indian Ocean, than over the monsoon region, while the reduced convection in break phase propagates faster from ocean to land and persists there for a longer time. Compared to break events, active events have slower (faster) propagation over the monsoon (oceanic) region during El Nino decay years. The present study put forward the argument that the contrasting persistent circulations over Indo-western Pacific regions favour particular phase of intra-seasonal oscillation (ISO) in developing and decay phase of El Nino. These long-lasting circulations advect anomalous dry (moist) air to ISM region for longer period, resulting in long-lasting break (active) events in El Niño developing (decay) years. During co-occurrence years, the number of break (active) days is reduced by two to three times compared to the developing (decaying) phase of El Niño. It is found that 30- to 60-day scale ISO is strongly modulated, than 10 - to 20-day scale, by the changes in seasonal mean state associated with El Nino. Thus, this study demonstrates that the ISO characteristics such as its variance, northward propagation, spatial distribution and duration of active and break days are strongly modulated by seasonal background anomalies over the Indo-Pacific region.

Description: ABSTRACT The World Meteorological Organization (WMO) Lead Centre for Long-Range Forecast Multi-Model Ensemble (WMO LC-LRFMME) has been established to collect and share long-range forecasts from the WMO designated Global Producing Centres (GPC). In this study, the seasonal skill of the deterministic multi-model prediction of GPCs in WMO LC-LRFMME is investigated. The GPC models included in the analysis cover 30 years of common hindcast period from 1981 to 2010 and real-time forecast for the period from DJF2011/2012 to SON2014. The equal-weighted multi-model ensemble (MME) method is used to produce the MME forecast. We show that the GPC models generally capture the observed climatological patterns and seasonal variations in temperature and precipitation. However, some systematic biases/errors in simulation of the climatological mean patterns and zonal mean profiles are also found, most of which are located in mid-latitudes or high latitudes. The temporal correlation coefficients both of 2 m temperature and precipitation in the tropical region (especially over the ocean) exceed 95%, but drop gradually towards high latitudes and are even negative in the polar region for precipitation. The prediction skills of individual models and the MME over 13 regional climate outlook forum (RCOF) regions for four calendar seasons are also assessed. The prediction skills vary with season and region, with the highest skill being demonstrated by the MME forecasts for the regions of the tropical RCOFs. These predictions are strongly affected by the ENSO over Pacific Islands, Southeast Asia and Central America. Additionally, Southeast of South America and North Eurasian regions show relatively low skills for all seasons when compared to other regions.

Description: ABSTRACT This study examines the trends in reference evapotranspiration (ET o ) in Turkey by analysing data from 77 weather stations for a 32-year period (1975–2006). ET o values were calculated using the Penman–Monteith method using air temperature, wind speed, relative humidity, and sunshine hours data. Trends in annual and monthly ET o were determined using the Mann–Kendall trend test with the trend-free prewhitening procedure. The magnitude of trends was estimated by calculating the Sen's slope. The collective or field significance of the trends was evaluated using Walker test. The possible causes of changes in ET o were discussed by analysing the trends in air temperature, wind speed, relative humidity, and solar radiation data collected at the same stations. The implications of ET o trends for crop water requirements were evaluated. The analyses showed that the majority of stations (88%) in Turkey had annual ET o between 750 and 1200 mm during the 32-year period and ET o decreased gradually from south to north. From 1975 to 2006, 58% of stations had upward trends in annual ET o . Upward trends were statistically significant at the 0.05 level for 32% of stations. The rates of changes in annual ET o were on average 1.20 mm year −2 . The trends detected in monthly ET o were mostly upward with an average magnitude between −0.01 and 0.14 mm month year −1 . Trends detected at the annual timescale and for the majority of the months provided the field significance at the 0.05 level. Analysis of other climatic data showed that upward trends in air temperatures, downward trends in wind speeds, and downward trends in relative humidity were widespread over Turkey for the same time period. Changes in these three parameters could explain the majority of the changes in ET o rates. The ET o changes affect crop water requirements and increase the demand for irrigation.

Description: ABSTRACT We explore the occurrence of intraseasonal summer heat waves in southeastern Patagonia (SEPG, 46°–52°S; 65°–70°W) since the late 19th century by means of the Twentieth Century Reanalysis version 2 (20CRv2). In total, we identify 201 cases for 1872–2010 using criteria of intensity and persistence. In SEPG, the corresponding intraseasonal temperature signals are centred around the first day of each cluster of days fulfilling those conditions (named day 0). The mean warm deviation lasts for approximately 2 weeks and exhibits a mean temperature peak of 4.3 °C on day 0 (the warmest day in the mean signal). In a regional context, the mean temperature perturbation associated with these heat waves affects a broad area on both sides of the Andes. The warming in SEPG is caused by temperature advection and enhanced radiative heating, following a high pressure system over southern South America (SSA). This atmospheric perturbation is embedded in a wave-train-like pattern along the South Pacific. As part of this pattern, a cyclonic anomaly progresses eastward over the Tasman Sea in Oceania, moving from southeastern Australia (day −6, causing a dry anomaly there) over New Zealand (day −3, inducing a wet anomaly on its Southern Island). The anomalous circulation triggered by the wave train leads thus to a teleconnection between SSA and Oceania, documented in a previous work for the interannual scale. Two thirds of the heat wave events are linked to enhanced ascent in the South Atlantic Convergence Zone (SACZ) and around one third of the events within 1957–2010 are associated with extreme absolute maximum temperatures observed at a station-based record from SEPG. Finally, possible spatial modulations of the wave train pattern at the interannual and interdecadal timescales are discussed.

Description: ABSTRACT The Pacific-Japan (PJ) pattern affects interannual variability in the East Asian and western North Pacific (WNP) summer monsoons. This teleconnection pattern is characterized by a meridional dipole of anomalous circulation and precipitation between the tropical WNP and the midlatitudes. This study develops a long index of the PJ pattern using station-based atmospheric pressure data to track the PJ variability from 1897 to 2013. This index is correlated with a wide array of climate variables including air temperature, precipitation, Yangtze River flow, Japanese rice yield and the occurrence of tropical cyclones over the WNP (especially those that make landfall on the Chinese and Korean coast). For the recent three decades, the PJ index reproduces well-known correlations with El Niño-Southern Oscillation (ENSO) in the preceding boreal winter and Indian Ocean temperature in the concurrent summer. For the 117-year period, this ENSO-PJ relationship varies on interdecadal time scales, with low correlations in the 1920s and from the 1940s to 1970s, and recurrences of significant correlations at the beginning of the 20th century and the 1930s. In accordance with the modulation, the magnitude and regional climate effect of the PJ variability have changed. These results highlight the importance of interdecadal modulations of climate anomalies in the summer WNP and the need of long-term observations to study such modulations.

Description: ABSTRACT The aim of this article is to present a methodology that describes the relationship between two time series according to their oscillatory modes. Cross-wavelet analysis is used to analyse the connection between the outputs of the empirical mode decomposition (EMD). The combined EMD and cross-wavelet methodology is used for the description of the connection between the annual mean streamflow of Quebec rivers and the North Atlantic Oscillation index (NAO). The relationship between the two time series is analysed by cross-wavelet analysis at the level of the mode of oscillation extracted from the EMD algorithm. The resulting cross-spectra are obtained individually for 18 stations and show intermittent intensity in these relationships between 1970 and 1990 for different oscillation modes. To highlight its particularity, the present methodology is compared with the results of a similar combination of multiresolution analysis (MRA) and cross-wavelet analysis. It shows that EMD isolates clearer bands of frequencies than MRA. Finally, a multi-site analysis is proposed, which performs a principal component analysis of the cross-spectra. This analysis illustrates the evolution of the relationships according to the geographic location. Finally, the advantages and limitations of the proposed methodology are discussed.

Description: ABSTRACT Hot summer days may lead to reduced thermal discomfort, labour productivity, and higher morbidity and mortality for vulnerable groups. The projected climate change may raise this thermal discomfort in the future. To implement measures to prevent adverse health conditions, robust estimates of the future human thermal comfort (HTC) are required. This study analyses the future HTC for both coastal and inland Dutch cities and countryside. The future conditions are based on the KNMI-06 climate scenarios. Using these scenarios, observed weather data from 1976 to 2005 are transformed to future weather design data representative for 2050. Subsequently, HTC expressed in the physiological equivalent temperature (PET) is estimated for these future scenarios. A substantial increase of heat stress abundance is foreseen in all climate scenarios, for both urban and rural areas, particularly, under the most intense warming. In these scenarios, the frequency of hours with heat stress will more than double, and the increase will develop faster in an urban canyon than in rural areas. In urban areas, PET shows a maximum as function of sky-view factor (SVF), i.e. for a smaller SVF a wind speed reduction increases the PET on one hand and shading reduces the PET on the other hand.

Description: ABSTRACT El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out an analysis of maize yield variability in IP for the whole 20th century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate-dependent time series of crop yield for the whole region, and to use these yield to analyse the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature–yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Description: ABSTRACT There is growing evidence of significant changes in components of the Antarctic climate system, an important issue given the influence Antarctica has on global climate. It is important to infer to what extent these regional changes could be attributed to human-induced processes and to what extent to natural variability. Standard methods such as linear trend estimates or piecewise linear trends can be inadequate because they may result in erratic, non-systematic results, particularly if different scales of variability are present in each record and various records are to be compared. The Orcadas Antarctic Station (Argentina), with daily surface meteorological observations since April 1903, provides Antarctica's longest observational record. This study analyses the Orcadas seasonal surface temperature variability. Multidecadal variability and short-term trends are studied to provide an improved assessment of climate evolution and necessary information for the determination of mechanisms driving regional/local change. A combined method using wavelet transform (WT), non-linear statistical model approaches and derivative of fits is developed. This methodology is also applied for validation and comparison to the Gomez ice core oxygen isotope record for the 1857–2006 and 1903–2006 time intervals. Significant quasi 50-year and quasi 20-year variability bands were obtained, both for the quarterly and seasonal Orcadas temperature records, with warming (cooling) periods detected between 1903–1912, 1927–1961 and 1972–2004 (1912–1927 and 1962–1972). If seasons are considered, the only one with a fairly sustained warming is summer, where actual cooling is observed only at the beginning, prior to the early 1930s. Quasi 50-year variability was also detected in the Gomez record. Long periods are obtained in the model fits, longer than the time series, which varied with window length. Although not representing variability cycles, they could represent the best fit of the non-linear, non oscillating asymptotic stationary component of the series, i.e. a non-linear trend.

Description: ABSTRACT This article presents a climatology of total cloud cover (TCC) in the area of the three inland Eurasian seas (Black, Caspian, and Aral Sea). Analyses are performed on the basis of 20 years of data (1991–2010), collected from almost 200 ground stations. Average TCC is 49%, with broad spatial and seasonal variability: minimum TCC values are found in summer and to the southeast, whereas maximum values correspond to winter and to the northwest. For the whole area, linear trend analyses show that TCC did not vary during the study period. We only detected a statistically significant positive trend (+1.2% decade −1 ) in autumn. We obtained different results for the regions delimited by means of a principal component analysis: a clear decrease, both for the annual, spring, and summer series, was detected for the south of Black Sea, while increasing TCC was found for the annual, autumn, and winter series in the north Caucasus and the west and north of Black Sea. We also analysed the TCC data from global gridded products, including satellite projects [International Satellite Cloud Climatology Project (ISCCP), Pathfinder Atmospheres Extended (PATMOS-x), cLoud, Albedo & Radiation (CLARA)], reanalyses [ERA-interim, National Centers for Environmental Prediction/Department of Energy (NCEP/DOE), Modern-Era Retrospective Analysis for Research and Applications (MERRA)], and surface observations [Climatic Research Unit (CRU)]. Although all these products capture the seasonal evolution over the study area, they differ substantially both among them and in relation to the ground observations: reanalyses produce much lower values of TCC, while ISCCP and CLARA provide a summer minimum that is too high. Trend analyses applied to these data generally showed a decrease in TCC; only CRU and NCEP/DOE tally with the ground data as regards the absence of overall trends. These results are discussed in relation to previous studies presenting trends of other variables such as sunshine duration, diurnal temperature range, or precipitation; we also discuss the connections with changes in synoptic patterns and environmental changes, in particular in the Aral Sea region.

Description: ABSTRACT The Southern Annular Mode (SAM) is a natural climate mode of variability whose discovery can be traced back at least as far as the beginning of the 20th century, before human activities produced enough gases to noticeably change the climate. However, recent observed changes in the SAM are linked to increases of greenhouse gases and stratospheric ozone depletion, hence assigning SAM's alterations, in large part, to human activities. In this study, the 20th century reanalysis data were used to establish the SAM's prominent shifts during the years 1917, 1961 and 1997. The first shift coincides with abrupt greenhouse gas increases and the latter shifts are attributed to stratospheric ozone level changes. The East Africa ‘Short Rains’ (EASR) index derived from the Global Precipitation Climatology Center (GPCC) dating back to the beginning of the 20th century, demonstrates coinciding shifts with the SAM index. However, the SAM's influence on EASR appears to be achieved through a meridional dipole that is formed in the sea-level pressure of the Indian Ocean basin, with one pole over the Tropics and the other over the extratropics. When this dipole pattern is weakly developed as the period between 1961 and 1997, the SAM is decoupled from the EASR and the Indian Ocean Dipole (IOD) demonstrates a dominant role in modulating the EASR. The SAM is also linked to the IOD through its control of the Mascarene High variability, hence connecting the SAM to the dominant circulation variability in the Indian Ocean. Although the El Nino Southern Oscillation is strongly correlated to EASR, it is not related to the epochal variability in the rainfall. Therefore, the slow modulation in EASR is linked to the SAM whose shifts are triggered by gases emanating from human influences.

Description: ABSTRACT The Hawaiian Islands have one of the most spatially diverse rainfall patterns on earth. Knowledge of these patterns is critical for a variety of resource management issues and, until now, only long-term mean monthly and annual rainfall maps have been available for Hawai‘i. In this study, month-year rainfall maps from January 1920 to December 2012 were developed for the major Hawaiian Islands. The maps were produced using climatologically aided interpolation (CAI), where the station anomalies were interpolated first, and then combined with the mean maps. A geostatistical method comparison was performed to choose the best interpolation method. The comparison focuses on three kriging algorithms: ordinary kriging (OK), ordinary cokriging (OCK), and kriging with an external drift (KED). Two covariates, elevation and mean rainfall, were tested with OCK and KED. The combinations of methods and covariates were compared using cross-validation statistics, where OK produced the lowest error statistics. Station anomalies for each month were interpolated using OK and combined with the mean monthly maps to produce the final month-year rainfall maps.

Description: ABSTRACT E-OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia. However, for studying regional or local climatic effects, a finer resolution would be more appropriate. A continental data set with resolution would allow research that is large in scale and still locally relevant. Until now, a climate data set with high spatial and temporal resolution has not existed for Europe. To fulfil this need, we produced a downscaled version of E-OBS, applying the delta method, which uses WorldClim climate surfaces to obtain a 0.008 ° (about 1 × 1 km) resolution climate data set on a daily time step covering the European Union. The new downscaled data set includes minimum and maximum temperature and precipitation for the years 1951–2012. It is analysed against weather station data from six countries: Norway, Germany, France, Italy, Austria, and Spain. Our analysis of the downscaled data set shows a reduction in the mean bias error of 3 °C for mean daily minimum temperature and of 4 °C for mean daily maximum temperature. Daily precipitation improved by 0.15 mm on average for all weather stations in the validation. The entire data set is freely and publically available at ftp://palantir.boku.ac.at/Public/ClimateData .

Description: ABSTRACT In this study, we investigated changes in the precipitation characteristics for China from 1960 to 2012 based on a recent daily precipitation dataset of 666 climate stations and robust non-parametric trend detection techniques. We divided all precipitation events into four non-overlapping categories: light, moderate, heavy and very heavy based on percentile thresholds. We then established the trends for annual total and precipitation of different intensity categories, and examined their regional and seasonal variations. The results show that there was little change in annual total precipitation for entire China, but distinctive regional patterns existed. In general, precipitation increased in the west and decreased in east. Precipitation of different intensities, in general, changed in the same direction as the mean, but heavy and very heavy precipitation events had higher rates of change than mean precipitation. The exception was the southeast region, where despite the slight decrease in mean precipitation, heavy and very heavy precipitation still increased significantly. In addition, we used multiple regression models to explore the contribution of changes of frequency and intensity to total precipitation change, and the contributions of changes of precipitation at different intensities to total precipitation change. For western China, total precipitation change was associated more with frequency change, whereas in eastern China intensity contributed more. For precipitation amount, moderate, heavy and very heavy precipitations contributed to the total change, with little contribution from light precipitation change. For frequency, changes in light and moderate precipitation frequencies dominated the total change, with very little contributions from heavy and very heavy precipitation frequency changes. In addition, we examined the linkage between summer precipitation in eastern China and the East-Asian Summer Monsoon (EASM), found that the northern decrease and southern increase in summer precipitation was likely caused by the weakening of EASM over the study period.

Description: ABSTRACT Southeastern South America (SESA) rainfall is influenced by the tropical Pacific, Atlantic and Indian Oceans. At the same time, these tropical oceans interact with each other inducing sea surface temperature anomalies in remote basins through atmospheric and oceanic teleconnections. In this study, we employ a tool from complex networks to analyse the collective influence of the three tropical oceans on austral spring rainfall variability over SESA during the 20th century. To do so we construct a climate network considering as nodes the observed Niño3.4, Tropical North Atlantic (TNA), and Indian Ocean Dipole (IOD) indices, together with an observed and simulated precipitation (PCP) index over SESA. The mean network distance is considered as a measure of synchronization among all these phenomena during the 20th century. The approach allowed to uncover two main synchronization periods characterized by different interactions among the oceanic and precipitation nodes. Whereas in the 1930s El Niño and the TNA were the main tropical oceanic phenomena that influenced SESA precipitation variability, during the 1970s they were El Niño and the IOD. The influence of El Niño on SESA precipitation variability might be understood through an increase of the northerly transport of moisture in lower-levels and advection of cyclonic vorticity in upper-levels. On the other hand, the interaction between the IOD and PCP can be interpreted in two possible ways. One possibility is that both nodes (IOD and PCP) are forced by El Niño. Another possibility is that the Indian Ocean warming influences rainfall over SESA through the eastward propagation of Rossby waves as suggested previously. Finally, the influence of TNA on SESA precipitation persists even when the El Niño signal is removed, suggesting that SST anomalies in the TNA can directly influence SESA precipitation and further studies are needed to elucidate this connection.

Description: ABSTRACT How boreal summer intraseasonal oscillation (BSISO) modulates the probability and spatial distributions of extreme rainfall occurrence over populous southern China was examined, using the newly proposed BSISO indices and two high-resolution rain-gauge-based rainfall datasets in China. The probability density function of May–August rainfall in southern China is skewed towards large values in phases 2–4 of the first component and in phases 5–7 of the second component of BSISO life cycle, during which the probability of extreme rainfall events at the 75th (90th) percentile increases by 30–50% (over 60%) relative to the non-BSISO period. The devastating floods with prolonged extreme rainfall in southern China over the three past decades occurred coincidently with these BSISO phases. The first component of BSISO, associated with 30–60-day eastward/northeastward-propagating ISO, is more favourable for the rainfall extreme over in-land China. In contrast, the second component of BSISO, related to the 10–30-day northwestward propagating ISO, tends to link with the rainfall extreme along the southeast coast of South China. Moisture budget indicates that the favourable environment for rainfall extreme is associated with southwesterly moisture convergence over southern China, while the moisture advection contributes insignificantly. This study suggests a potential for monitoring and probabilistic prediction of extreme rainfall events in southern China based on the real-time BSISO indices.

Description: ABSTRACT The sea surface temperature (SST) in the Bay of Bengal (BoB) during the period 1960–1995 showed a decadal cycle, riding over a warming trend. The disruption of the decadal cycle was noticed post-1995 and was followed by a slowdown in the sea surface warming. The cause for the disruption of the SST decadal cycle was the weakening of the link between SST and sunspot number. The rising trend in the SST is due to the increasing atmospheric CO 2 concentration. The post-1995 SST slowdown was due to the increasing influence of the number of depressions, cyclones and severe cyclones in the BoB, the occurrence of which showed an upward trend. Using Price–Weller–Pinkel model we show that cyclonic systems deepen the mixed-layer through enhanced mechanical-mixing with cooler sub-surface waters, thereby reducing the mixed-layer temperature and consequently the SST. This process opposes the SST rise due to increasing atmospheric CO 2 concentration. The net effect of the wind-mixing caused by the increased number of depressions, cyclones and severe cyclones and the increased CO 2 concentration is a SST slowdown in the BoB. This mechanism differs from the SST slowdown mechanisms suggested for the Atlantic and the Pacific.

Description: ABSTRACT In the last few years, there has been an increasing application of gridded precipitation data sets for studies analysing seasonal and interannual precipitation variability as well as for performing validation analysis of climate and regional models. Consequently, the purpose of the present study is to analyse the representation of temporal variability and spatial patterns of precipitation in South America for the period 1971–2010, derived by three data sets based exclusively on rain gauge information (Climate Research Unit – CRU, Global Precipitation Climatology Centre – GPCC and University of Delaware – UDel), in order to identify discrepancies and/or agreements among them. Further analysis is performed for three particular sub-regions within the continent (southern sector of southeastern South America – SSESA, central South America – CSA and southeastern Brazil – SEBR). Results show that the three products represent key spatial features of precipitation analogously. Significant coherence in capturing the temporal variability, associated with the dominant modes of variability, is found in all sub-regions, though they differ largely in some areas, especially in CSA. Overall, depending on the region, the gridded products behave differently, without one particular data set standing out as an outlier in all the analysed cases.

Description: ABSTRACT Land and water management in semi-arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5-day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.

Description: ABSTRACT Precipitation variability at inter- and intra-annual scales may influence land-use management decisions in semi-arid savannas worldwide, and in particular, over the Kavango-Zambezi Transfrontier Conservation Area (KAZA) in southern Africa. Over KAZA, spatiotemporal precipitation variability forced by the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) is important to local and regional-scale decisions for planting, livestock grazing, and wildlife migration patterns. We investigate the annual water year (October–September) and early rainy season [October–November–December (OND)] precipitation patterns during 60 years before and after a 1970s shift in the global ocean–atmosphere system for this region in southern Africa. The coincidence of the number of wet (upper tercile) and dry (lower tercile) years and OND seasons during the various phases of ENSO and IOD are compared prior to (1950–1975) and after (1980–2008) the 1970s climate shift over KAZA. Since the 1970s climate shift, KAZA has been significantly drier and observed fewer wet years and OND seasons. ENSO is the dominant forcing of precipitation differences over southern Africa before and after the 1970s climate shift, with IOD playing a secondary role. However, when ENSO and IOD phases are analysed simultaneously, El Niño and positive IOD events are significantly related to dry periods. The forcing of atmospheric circulation over southern Africa before and after the 1970s climate shift during El Niño and La Niña events is significantly different. Prior to the 1970s climate shift, atmospheric circulation during El Niño (La Niña) favoured strong (weak) precipitation increases (decreases). Afterward the 1970s climate shift, atmospheric circulation during La Niña (El Niño) favoured strong (weak) precipitation decreases (increases). The shifting nature of climate modes, especially ENSO, and respective influence on rainfall variability for southern Africa is important to understand to better inform seasonal climate forecasts to improve operational decision-making for land-use and water management decisions in semi-arid savanna regions.

Description: ABSTRACT A unique approach for downscaling daily precipitation extremes from historical analogues is presented. While various analogue methods have been developed for the purpose of downscaling local climate data, few have placed an emphasis on downscaling daily extremes. Unlike previous approaches, the new method utilizes a two-step procedure in which the occurrence of extreme precipitation on a given target day is first determined based on the observed probability of extreme precipitation on that day's closest historical analogue days. Then, if extreme precipitation occurred on the selected analogue day, the historical precipitation observations associated with the analogue day are used to ascribe precipitation amounts on the corresponding target day. The method is developed and tested for a very strict definition of extreme precipitation (partial duration series events), as well as a more lenient definition of extreme precipitation (95th percentile of non-zero precipitation events). The analogue approach is more skillful than climatology at identifying the occurrence of both partial duration series (PDS) and 95th percentile events. In both cases, the analogue method slightly underestimates the observed occurrence of extreme precipitation. Return period precipitation amounts estimated from the downscaled PDS are similar to, but generally lower than those calculated from observed PDS. Over the entire study domain (157 stations in New York State and surrounding regions of adjacent states and Canada), the median difference between downscaled and observed 5-year (100-year) return period precipitation amounts is less than 5% (10%). These median differences are smaller than those obtained from historical dynamically downscaled climate model simulations.

Description: ABSTRACT The summer time cloud diurnal cycle over western Iberia is analysed here using a satellite climate data record of fractional cloud cover based on 9 years of Meteosat Second Generation observations which is distributed by the EUMETSAT's Climate Monitoring Satellite Applications Facility. These observations were complemented with a corresponding mean cloud diurnal cycle using SYNOP reports on six locations over the studied domain. It is shown that the main coastal mountain range separates regions that are characterized by two very different cloud regimes: stratocumulus-topped boundary layer convection dominates the region towards the coast and continental cumulus convection dominates the region to the east of these mountains. To explain the observed variability, a long-term regional climate model [Weather Research and Forecasting model (WRF)] simulation over Iberia was used. A comparison of the observations against model output for the common period between observations and simulation shows that although the model generally underestimates cloudiness, it is able to represent the diurnal cycle in a realistic manner. It is shown that the observed cloud diurnal evolution is linked to the thermal circulations generated by the land-sea contrast and orography. The extent to which the cloud deck penetrates inland is closely related to the coastal orography: although smaller hills tend to enhance cloudiness, larger mountains block the progression of the marine boundary layer further inland, as it behaves as a density current. Larger mountains also produce katabatic flow and a rather strong subsidence aloft during the night. The warming due to this subsidence helps the blocking of the cloud deck as it is partially responsible for evaporating clouds, as shown by a potential temperature budget analysis.

Description: ABSTRACT High-quality temperature estimates with good spatio-temporal coverage are necessary for completely understanding the influences of warming climate on cryosphere and hydrological systems in High Mountain Asia (HMA). In this study, we compare reanalysis temperature data from ERA-Interim and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) with station observations in HMA during 1979–2011. The results indicate that although reanalysis temperature data can capture the warming trends in HMA, the trend magnitudes are clearly underestimated by reanalysis data. In particular, the increase in summer temperature cannot be identified from the NCEP/NCAR reanalysis. For ERA-Interim, temperature increases are underestimated in the north and northwest of HMA; for NCEP/NCAR, the warming magnitudes show evident biases in the Pamir, Himalayas, and southeastern Tibetan Plateau. Considering that high-frequency signals and periodical fluctuations among the three datasets are in good agreement, and based on the wavelet transform method, the low-frequency component decomposed from the temperature time series of ERA-Interim and NCEP/NCAR reanalyses is adjusted by that derived from station observations. The resulting homogenized reanalysis temperature data show much better spatio-temporal consistency with station data. The differences in monthly and annual temperature anomalies between station and homogenized ERA-Interim and NCEP/NCAR reanalysis data become more convergent. The homogenized temperature time series are better correlated with station data at annual and seasonal timescales.

Description: ABSTRACT The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33-year (1979–2011) wind data from the Climate Forecast System Reanalysis (CFSR) that has many improvements including higher spatial resolution over previous global reanalysis products. Mean 80-m wind speeds are consistently higher over China Seas and the ocean areas than over land, and inside China high winds are found in areas of Inner Mongolia and the Tibetan Plateau. There is a considerable seasonal variability that reflects primarily the influence of East and Southeast Asia Monsoon with generally higher speeds in winter followed by summer, and weaker winds in autumn, followed by spring. There is also a strong interannual variability, and regions of larger amplitude of variability coincide with regions of higher mean winds. A decreasing trend, dominated by a sharp decline beginning in 2005, is seen across China and the surrounding seas in summer and autumn, and the summer trends over land and over ocean appear to be related respectively to the Pacific Decadal Oscillation (PDO) and the East Asian summer monsoon. Trends are not consistent across the region in spring and winter, however, with positive trends over some areas in northeastern and northwestern China, Mongolia and tropical oceans whereas negative trends in other regions. Nearly all areas of China experience mean annual 80-m wind speed less than 6.9 m s −1 (wind power classes of 1–2) except for some areas of Inner Mongolia where mean annual 80-m wind speeds exceed 6.9 m s −1 (Classes 3 or higher, suitable for wind energy development). China Seas and ocean areas generally fall in Class 3 or above, with the Taiwan and Luzon Straights reaching the highest Class 7.

Description: ABSTRACT Capturing the intensity and return period of extreme rainfall events in the historic record and projecting them into the future are essential to managing, planning, and designing infrastructure. In this study, we assess the performance of the combination of four General Circulation Models (GCMs) and six Regional Climate Models (RCMs) that comprise the North American Regional Climate Change Assessment Program (NARCCAP) and evaluate their performance in simulating rainfall extremes in the continental United States. We adopt a regionalization method to objectively delineate 12 regions in the continental United States with relatively homogenous annual maximum 24-h rainfall patterns from the North American Regional Reanalysis (NARR) data set. We then compare the Intensity–Duration–Frequency (IDF) curves generated from control simulations of NARCCAP models with those from NARR in each of these regions. We find significant spatial variability of model performance. The models perform reasonably well in many parts of the country, but poorly in the southeastern United States. The GCM providing boundary conditions strongly influences results – output from those RCMs driven by the Community Climate System Model (CCSM) and Canadian Global Climate Model version 3 (CGCM3) matched the NARR data best. Performance of individual RCMs also varied, often in response to nudging, wherein the regional model is constrained by the GCM fields. We also measure changes in bias-corrected IDF curves generated from NARCCAP projections of the future. In most regions, most models project intensified 24-h rainfall events in the future (exceptions include some model-projected decreases in southern California, the extreme north-central US, Florida, and the Texas Plains). This study provides a valuable means of assessing NARCCAP models' performance in simulating rainfall extremes at the regional scale and understanding how the GCMs, RCMs, and spatial variability affect model performance.

Description: ABSTRACT Climate data from the southwest coast of the Caspian Sea (CS) were statistically analysed to find connections with large-scale atmospheric variabilities and regional impacts. The study area is characterized by a subtropical humid climate. This enclave of high precipitation is extremely important for Iranian food production and is recognized for its high biodiversity. The data sets were investigated for inconsistencies before carrying out the main investigations, and several problems have been identified. The results show three distinct climatic periods in the temperature time series since 1956: 1956 to 1975 with values near to the overall mean, 1977 to 1995 with values lower by 0.5 °C and from 1996 to 2010 with values higher by 0.5 °C. These periods can be positively correlated with rapid sea level changes of the CS. Moreover, an agreement exists between the three climatic periods and the North Atlantic Oscillation (NAO) variability. The sea surface temperature of the southern CS is shown to be the driving force of the 2 m temperatures in the study area. While temperature changes are in accordance with NAO variability, the precipitation variations show connections with ENSO and less with NAO. The trends of precipitation during the period are diverse but display mostly a weak decrease, while the trends of temperature display a clear increase, larger than that for global mean temperatures, overlaid with inter-decadal variations.

Description: ABSTRACT This paper studies how the anthropogenic-induced global warming affects the East Asian winter monsoon (EAWM) by using 26 Coupled Model Intercomparison Project phase 5 (CMIP5) models. The simulated present-day EAWM is evaluated and future projections under RCP4.5 and RCP8.5 scenarios are presented in terms of the climatology and interannual variability. All 26 models can well reproduce the spatial pattern of EAWM climatology and 16 out of the 26 models can reasonably capture major features of interannual variability. The projection made by 26-model ensemble mean indicate that winter surface air temperature averaged over 20°–60°N, 100°–140°E will increase by 3 °C in RCP4.5 and 5.5 °C in RCP8.5 towards the end of the 21st century. The corresponding regional mean precipitation will increase by 12.3% in RCP4.5 and 21.8% in RCP8.5. The strong warming over high-latitude North Pacific due to melting sea ice in the Bering Sea and Okhotsk Sea leads to significant intensification and a northward shift of the Aleutian Low, resulting in prominent increase in the low-level northerly along the coastal regions of northeastern Asia. At 500 hPa the characteristic East Asian Trough is projected to weaken slightly and tilt more eastward with latitude. The selected 16-model ensemble mean projects future enhanced interannual variability of surface air temperature and sea-level pressure over mid-latitude North Pacific and high-latitude East Asia (EA) and reduced variability over eastern China, suggesting that the EAWM will be more variable in the high-latitude EA and mid-latitude North Pacific but less variable in East China. Accordingly, the year-to-year precipitation variability will be significantly enhanced over high-latitude EA. Majority of the 26 models project that the leading mode of EAWM interannual variation (the ‘northern mode’) will become more dominant in the warmer climate.

Description: ABSTRACT Crop loss due to drought is a complex issue, because it changes according to the drought intensity and duration, and the developmental stage of the plants when drought occurs. In order to assess the drought-induced decline in crop harvest, drought variability and the yield sensitivity of winter wheat, maize, sugar beet, and sunflower to drought during their growing seasons is investigated in the Republic of Moldova. This is then used as an example of the response of non-irrigated crops to increasing drought tendency in south-eastern Europe. The quantification of drought was done by using the standardized precipitation evapotranspiration index (SPEI) at 1- to 12-month lags during the period from 1951 to 2012. The relationship between drought at various time scales and the standardized yield residuals series (SYRS) for individual crops over the country and the Balti chernozem steppe of Moldova (represented by Balti experimental site) for the 1962–2012 farming years were investigated. In order to detect the trends and the shifts in the SPEI time series over 62 years, the non-parametric, Mann–Kendall and Pettitt tests were used for each month of the year to cover the main life cycle of the crops. The trend analysis of agricultural drought emphasizes an increasing trend from June to October, and becomes significant in the southern region at the 95% level during July to September. The SPEI highlights the main periods of dry/wet persistence and the regional characteristics of drought which are present in the Southern region, and make this region more prone to severe drought persistence, mostly during the last decade. Drought during the plant reproductive stages may significantly reduce grain yield potential, the relation between the SYRS and the SPEI explaining up to 62% of the low-yield variability.

Description: ABSTRACT In the face of limited or no precipitation data, global precipitation data sets (GPDs) may provide a viable alternative to gauge or ground radar data. This study aims to provide guidance to the choice of GPDs targeting scales relevant to water resources management in data poor regions. Specifically, the 34 000 km 2 Kilombero Valley in central Tanzania, where water resource management is seen as integral to poverty reduction and food security, is used as a case study for performance evaluation of seven GPDs and their ensemble mean against the Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis research-grade product v7 (TRMMv7). The GPDs include one satellite rainfall product [Climate Prediction Center morphing technique v1.0 CRT (CMORPH)], three reanalysis products [Climate Forecasting System Reanalysis (CFSR), European reanalysis interim (ERA-i) and Modern Era Retrospective-Analysis for Research and Applications (MERRA)] and three interpolated data sets [Climate Research Unit Time Series 3.21 (CRU), Global Precipitation and Climatology Center v6 data set (GPCC) and University of Delaware Air Temperature and Precipitation v3.01 data set (UDEL)]. Standard statistical performance measures and spatial patterns were evaluated for the common overlap time period 1998–2010. For this region, the principal seasonality of the climatology was well represented in all GPDs; however, the intraseasonal variability and the spatial precipitation patterns were less well represented. The ensemble mean and GPCC had the best performance with regard to the analysis of the time series while CMORPH and GPCC had the best performance with regard to the spatial pattern analysis. These results indicate that the spatial scale intended for application is a major factor impacting the suitability of a given GPD for hydrometrological studies that form a basis for development of water management strategies.

Description: ABSTRACT This study investigates the effect of varying the vertical level of a synoptic circulation classification on its predictive skill with respect to surface temperature, rainfall, solar radiation and wind in Trentino, a mountainous region in the South-Eastern Alps. A synoptic climatology based on the same data set and classification method presented in part I of the present article, in fact, showed that seasonal anomalies of mean daily temperature, daily rainfall, daily solar irradiation and mean daily wind intensity vary not only among weather types and seasons but also within the same type and season for different vertical levels. This analysis quantifies the ability of the method to classify synoptic circulation in classes associated with distributions of atmospheric variables different from climatology and to identify the occurrence of extreme events. The statistical metrics presented in the article demonstrate that the differences in predictive skill between classifications applied to distinct levels are comparable in magnitude to those between different atmospheric variables and seasons for the same level. The level of 500 hPa generally provides the largest predictive skill with respect to total daily rainfall, daily solar irradiation and daily temperature range in all seasons. On the other hand, the largest skill with respect to wind intensity is found for sea level pressure and 850 hPa circulation types. Large seasonal variations are also evident, with the colder seasons providing the largest predictive skill. Combinations of circulation types derived at two vertical levels increase the skill, although an optimal combination of levels could not be found even for the same atmospheric variable and season.

Description: ABSTRACT In this paper, we analyse observed changes in characteristics of sub-daily heavy summer precipitation and erosive precipitation events for the Czech Republic, taking into consideration 51 years of data (1961–2011) for 17 stations. The sub-daily data were checked for consistency with the daily control records, and unreliable data were removed from the data set. Subsequently, four statistical tests were applied to assess the homogeneity of the data set. The trend magnitude was estimated using the Theil–Sen slope estimator, and two tests were applied to evaluate its significance. For most of the indices, the tests did not indicate inhomogeneity, with the exception of characteristics related to rainfall intensity. The trends are positive for most of the stations and most precipitation characteristics, and significant positive trends are much more frequent than negative trends. The analysis revealed a significant increase in the contribution of heavy precipitation to the precipitation total in half of the stations at short aggregation levels.

Description: ABSTRACT This study evaluates the simulation of the spring Arctic Oscillation (AO)-western North Pacific linkage based on the 16 state-of-the-art climate models from the Coupled Model Intercomparison Project Phase 5. The validation focuses on the predominant process connecting the spring AO with the East Asian summer monsoon: the formation and persistence of the spring AO-associated cyclonic anomaly over western North Pacific (WPCA) from spring to summer. The results indicate that 8 of 16 models can reproduce both the formation and persistence of the WPCA. Because the formation of the WPCA is directly related to the existence of the spring upper-level North Pacific atmospheric dipole (NPAD), the analyses suggest that a given model can reproduce the spring AO-associated NPAD if the model is capable of simulating the spring AO-associated deceleration of the subtropical westerly jet and the transient eddy activities around the westerly jet exit. Furthermore, the westerly jet anomalies are closely related to the simulated mean state of the westerly jet and the AO Pacific component, which could be further attributed to the simulated sea surface temperature biases over the equatorial Western Pacific.

Description: ABSTRACT Climate variability has major impacts on crop yields and food production in South Asia. The spatial differences of the impact are not, however, well understood. In this study, we thus aim to analyse the spatio-temporal relationship between precipitation and rice yields in the Ganges–Brahmaputra–Meghna region. The effects of rainfall variation on yields were analysed with regression models using the Standardized Precipitation Index (SPI) as an explanatory variable. Our results indicate that in large part of the study region, a strong relationship between precipitation and rice yields exists and the SPI at various lags chosen as the predictor variable performed well in describing the inter-annual yield variability. However, the study demonstrated large spatial variations in the strength of this relationship or optionally in the suitability of the chosen methodology for investigating it. In the mid-plains of the Ganges, which represent very important agricultural areas, precipitation variability has a strong impact on rice yields, while in downstream Ganges as well as in Brahmaputra, where precipitation is more abundant, the relationship was less pronounced. Where the performance of the regression models was weaker, it is likely that yield variation depended on other factors such as management practices or on other climate factors such as temperature. The results further showed that the SPI at 1, 3, 6 and 12 month lags calculated for the monsoon time (June–October) are most commonly the best at explaining the rice yield variability. The SPI can thus be considered a very useful predictor of rice yield variability in some parts of the study region, demonstrating that they could be used for agricultural applications and policy decisions to improve the region's food security.

Description: ABSTRACT Features and interdecadal variability of droughts were assessed over the East Asian monsoon region (20°–50°N, 103°–149°E) using the standardized precipitation index (SPI) and the gridded rainfall data set (1978–2007) at 0.5° resolution. To assess the spatial and temporal patterns of droughts, seven homogeneous rainfall zones that exhibit unique rainfall regimes and long-term variability over the region were used. The statistical analysis method known as the theory of runs was used to identify and characterize drought events. A run was defined as a portion of SPI drought series in which all values were below the selected threshold level. Run-length and run-sum were used to define the drought duration and drought severity, respectively. The study revealed unique drying and wetting patterns for different zones in the region. Interdecadal analysis of droughts over the past three decades revealed a significant increase in drought duration and severity in the low rainfall zones, whereas a significant decrease appeared in the high rainfall zones. In particular, the duration and severity dwindled to zero with no major drought event over the eastern and the East Sea coastal region of Japan during the last decade (1998–2007). These patterns pose serious threats of increasing droughts in the low rainfall zones and flooding in the high rainfall zones. The spectral analysis, using the Fast Fourier Transform, was performed to identify the cyclic patterns of SPI time series in each zone, which revealed dominant cycles of 15, 7.5, and 3.4 years in the different zones. These results suggest the possible influence of interdecadal Pacific Oscillations and North Atlantic Oscillations on droughts in the region, although these relations remain a challenging task.

Description: ABSTRACT Heavy rainfall months of more than 450 mm occur in all 56 meteorological stations in eight climatic zones of Vietnam during the rainy season from April to September in the north (〉20°N), from August to December in the centre and from May to November in the south (〈12°N). The severity of an El Niño Southern Oscillation (ENSO) episode, expressed as the integral of sea surface temperature anomaly (SSTA) in the central tropical Pacific over the duration, shows a 4.6-fold (2.3-fold) increase in number of heavy rainfall months during La Niña (El Niño) per unit change in severity during the 1960–2009 period, suggesting a twin peak occurrence with both ENSO extremes. A heavy rainfall index (HRI) links heavy rainfall months to the rainy season duration, and allows evaluation of the rainfall severity per station, climatic zone and ENSO cycle. For the deltas and central climatic zones, seasonal rainfall and number of heavy rainfall months are significantly higher at the p  〈 0.05 level during La Niña than during El Niño episodes. Interpolated seasonal rainfall shows distinct differences between regions, with location having a larger effect than ENSO cycles on monthly rainfall amounts. Twenty-year return monthly rainfall derived from generalized Pareto distributions for peak over thresholds range from 475 mm in the central highlands to 2185 mm in the central coast. The spatial and temporal patterns of heavy monthly rainfall help explain flooding and paddy inundation which occur at least twice as frequent during La Niña as compared to El Niño conditions, particularly in Central Vietnam. The relation of HRI with both 20-year return levels and ENSO cycles offers opportunities for fast screening of impacts in a wider region of Southeast Asia. Because ENSO cycles have an impact on flooding and paddy inundation, it provides prospects for early warning, differentiated for different zones and rainfall regimes.

Description: ABSTRACT Recent studies have pointed out the statistical occurrence of dual-season droughts detected in tree-ring chronologies over the southwestern US region that is not well described by instrumental observed records of the 20th century. In this study, a multi-statistical approach that evaluates persistent dual-season drought using a mode-of-variability oriented approach is proposed, considering a new network of tree-ring earlywood (EW)- and latewood-adjusted (LW adj ) chronologies from throughout southwestern North America. To determine dominant patterns of spatiotemporal variability, empirical, orthogonal functions, canonical correlation analysis, and multi-taper-method singular value decomposition analyses were applied, with focus on variability from inter-annual to centennial periods and highlighting the multi-decadal signals inherent to proxy record network. During the instrumental period, we demonstrate that EW and LW adj networks of tree-ring chronologies are able to capture the associated precipitation responses of cool and warm season atmospheric teleconnections. Considering the four-century period of the complete tree-ring network, we explore the possibility of a dual summer–winter variability signal in the low-frequency climate regime. EW and LW adj seem to be coherent in-phase at the very low-frequency scale (50–100 years spectral band). This provocative result is supported by major historic documented multi-year droughts of the region since 1650. Thus, the temporal variation of these chronologies time series and its associated spatial pattern strongly suggest that this low-frequency mode might represents an important spatiotemporal variation of droughts in the Southwest; however, the source of this signal is still an open question and of great interest for drought planning and resource management in the region.

Description: ABSTRACT Spatiotemporal patterns of precipitation regimes in terms of precipitation amount and number of precipitation days at different time scales are investigated using the entropy-based methodologies in the Huai River basin, China. Trends of precipitation variability are quantitatively evaluated using the modified Mann–Kendall trend test method. Correlations between the largest 7-day precipitation amount (R × 7day) and precipitation variability within 1 year are also analysed. Results indicate the following: (1) there is increasing nonuniformity of annual precipitation amount and annual precipitation days from south to north in the Huai River basin, indicating larger precipitation variability in the northern parts. Transition of precipitation changes is evident in the basin which is reflected by decreasing precipitation variability in the north and increasing precipitation variability in the south. (2) The disorder indices (DIs) exhibit variations at different time scales. In general, precipitation variability is larger at shorter time scales, such as daily, and is smaller at longer time scales, such as annual. (3) Significant relations are identified between the DI and extreme precipitation events, i.e. significant relations between apportionment DI and the largest 7-day precipitation amount and it is particularly the case in the central and southwestern parts. Thus, it can be said that higher precipitation variability is due to higher frequency of extreme precipitation regimes. Results of this study are of practical significance for planning and management of water resources and agricultural irrigation and agricultural activities during climate change and particularly for enhancement of measures for mitigation of consequences of climate change.

Description: ABSTRACT The aim of this study was to provide a better understanding of how vegetation and building geometry influence the spatial distribution of air temperature and nocturnal cooling rates (CR) in a high-latitude city. Intra-urban thermal variations were analysed in two seasons (May–September and November–March) and in different weather conditions (clear, calm and cloudy, windy) in Gothenburg, Sweden. Simultaneous air temperature measurements were conducted for 2 years (2012–2013) at ten fixed park and street sites characterized by varying type and amount of vegetation, building geometry, openness and surface cover. Several spatial characteristics, including sky view factor (SVF) as well as the cover and volume of buildings and trees, were calculated within circular areas of radii ranging from 10 to 150 m. Spatial characteristics were found to explain air temperature distribution in the studied area to a large extent throughout the day and year, in both clear, calm as well as cloudy, windy conditions. The highest correlations were found for weighted calculation areas accounting for the influence of both nearest (10 m) and wider (25–150 m) surroundings. Park sites remained cooler than built-up areas, with the most pronounced cooling effect (0.8 °C) on clear, calm days of the warm season. The most important factor governing CR around sunset was SVF. However, on clear, calm nights of the warm season, they were also enhanced by vegetation, indicating the influence of evapotranspiration. Minimum night-time air temperature was governed mostly by the presence of buildings. Within the street canyon, a daytime cooling and night-time warming effect of a street tree was observed, particularly in the warm season. The study shows the importance of various spatial characteristics describing openness, amount of vegetation and building geometry in analysing intra-urban variations in daytime and night-time air temperature.

Description: ABSTRACT This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three National Multi-Model Ensemble (NMME) models, and two coupled ocean–atmosphere or one-tiered models. These models are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature (SST) anomalies forecasted using constructed analogue SSTs (ECHAM4.5-SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012 and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 (ECHAM4.5-MOM3-DC2) and the ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST). The precipitation and 850 hPa geopotential height fields of the forecast models are statistically downscaling to the 0.5° × 0.5° spatial resolution of the Global Precipitation Climatology Centre (GPCC) Version 6 gridded precipitation data, using model output statistics (MOS) developed through the canonical correlation analysis (CCA) option of the Climate Predictability Tool (CPT). Retroactive validations for lead times of up to 3 months are performed using the relative operating characteristic (ROC) and reliability diagrams, which are evaluated for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record over the 15-year test period of 1995/1996 to 2009/2010. The forecast models' skills are also compared with skills obtained by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850 hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times of up to 3 months for autumn precipitation – the October-November-December (OND) season. For most seasons, a high skill is obtained from ECHAM4.5-MOM3-DC2 forecasts at a 1-month lead time when the models' 850 hPa geopotential height fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the observed and forecasts over the study area for the OND, November-December-January (NDJ), December-January-February (DJF) and January-February-March (JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectively.

Description: ABSTRACT The complexity, predictability and predictive instability of the Western Mediterranean Oscillation index (WeMOi) at monthly scale, years 1856–2000, are analysed from the viewpoint of monofractal and multifractal theories. The complex physical mechanism is quantified by: (1) the Hurst exponent, H , of the rescaled range analysis; (2) correlation and embedding dimensions, μ * and d E , together with Kolmogorov entropy, κ , derived from the reconstruction theorem; and (3) the critical Hölder exponent, α o , the spectral width, W , and the asymmetry of the multifractal spectrum, f ( α ). The predictive instability is described by the Lyapunov exponents, λ , and the Kaplan–Yorke dimension, D KY , while the self-affine character is characterized by the Hausdorff exponent, H a . Relationships between the exponent β , which describes the dependence of the power spectrum S ( f ) on frequency f , and the Hurst and Hausdorff exponents suggest fractional Gaussian noise (fGn) as a right simulation of empiric WeMOi. Comparisons are made with monthly North-Atlantic Oscillation and Atlantic Multidecadal Oscillation indices. The analysis is complemented with an ARIMA(p,1,0) autoregressive process, which yields a more accurate prediction of WeMOi than that derived from fGn simulations.

Description: ABSTRACT The complexity of impacts resulting from extreme precipitation events varies with the spatial extent of precipitation extremes. Characteristics of precipitation extremes, defined by the top 5% of 3-day accumulated precipitation, including their spatial coherence and relationships to two contrasting synoptic phenomena, were examined at stations across the Northwestern United States. The spatial coherence of precipitation extremes generally decayed with distance between stations. However, distinct geographic variability in region-wide coherence of precipitation extremes was present with overall higher coherence west of the Cascades, and lower coherence in the lee of the Cascades and Northern Rocky Mountains. Illustrative patterns of coherence were also seen with respect to atmospheric circulation regimes; atmospheric rivers favoured broadly coherent extremes occurring primarily west of the Cascades during fall and winter, while closed lows favoured more isolated precipitation extremes in the lee of the Northern Rocky Mountains and Cascades, occurring primarily during spring. Geographic variability in spatial coherence, direction of maximum coherence and seasonality of extremes suggest that extreme precipitation events result from the interaction of atmospheric circulation and complex topography.

Description: Situated along the coast of southern China and facing the South China Sea, Hong Kong has been experiencing a significant rise in sea level by about 2.9 mm year −1 since the 1950s. For a densely populated coastal city prone to storm surge impacts during the passages of tropical cyclones, accentuated by the threat of sea-level rise as a result of global warming and local vertical land displacement, projection of the sea-level change for Hong Kong is essential for local risk assessment and long-term planning of adaptation measures. This study presented the projection of sea-level change in Hong Kong and its adjacent waters under the Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios in the 21st century based on climate projections by models in phase 5 of Coupled Model Intercomparison Project, in combination with contributions from land ice and land water storage determined from published literatures, and local vertical land displacement as estimated by using continuous high-precision GPS observations in Hong Kong. The results show that the sea level in Hong Kong and its adjacent waters is projected to rise by 0.67 (0.50–0.84) m and 0.84 (0.63–1.07) m in 2081–2100 relative to 1986–2005 under RCP4.5 and RCP8.5, respectively, about 0.2 m higher than the global mean values projected by the Fifth Assessment Report of Intergovernmental Panel on Climate Change. The higher projected sea-level rise in Hong Kong and its adjacent waters as compared with the global mean values is primarily due to local vertical land displacement which contributes around 28% and 23% of the projected sea-level rise in 2081–2100 relative to 1986–2005 in the two respective RCP scenarios.

Description: ABSTRACT In this study, the detrended fluctuation analysis (DFA) method is used to analyse the drought and flood index (DFI) of the past 531 years in 20 stations over east central China. It is found that the variation of the DFI exhibits long-range correlation. The long-range correlation gradually decreases from northwest to southeast over the studied region. Moreover, the recurrence times of droughts or floods also show long-range correlation. The long-range correlation in the DFI data will disappear if the DFI data are randomly shuffled, which was also found in the recurrence time of the randomly shuffled DFI series for each station. The results show that long-range correlation is an intrinsic property of drought or flood events, which could result in the long-range correlation of the corresponding recurrence times. At present, the prediction skill of droughts/floods in Asian-Australian monsoon region is relatively low, particularly in most of China. The long-range correlation of the DFI provides a theoretical basis for climate predictions of droughts/floods and may help improve model performance by amending the model configuration, in terms of addressing parameterization problems and improving atmosphere–ocean coupling.

Description: ABSTRACT This work analysed the changes in air temperature in 25 meteorological stations in the Altiplano and the surrounding Andean slopes of Bolivia and Peru, and their relationship with El Niño-Southern Oscillation (SO) and the Pacific Decadal Oscillation (PDO). The analysis focused on annual, warm season (DJF) and cold season (JJA) maximum and minimum temperatures. All analyses were undertaken during 1965–2012, but some analyses were also from 1945 and 1955 when data were available. Principal component analysis was applied to the annual and seasonal series to identify spatial differences of changes in maximum and minimum air temperature. There was an overall increase of temperatures since the mid-20th century. The most intense and spatially coherent warming was observed for annual and warm season maximum temperature, with warming rates from 0.15 to 0.25 °C decade −1 . Changes in the cold season maximum temperature were more heterogeneous, and statistically significant trends were mostly in the Bolivian Altiplano. Minimum temperatures increased, but there was higher spatial variability and lower rates of warming. Maximum temperature was negatively correlated with the Southern Oscillation index (SO) in the warm season, and positively correlated with the SO in the cold season; there were less statistically significant correlations with the PDO, that exhibited inverse sign than those for SO. The strongest correlations were in the region near Lake Titicaca. The negative correlation of minimum temperatures with SO and the positive correlation of minimum temperatures with PDO were lower than the observed for maximum temperature. The changes in temperature and correlations with SO and PDO were highly dependent on the selected period, with stronger trends in the last 30–40 years. This suggests reinforcement of warming rates that cannot be only explained by SO and PDO variability.

Description: ABSTRACT In this study, we investigate the influence of global climate oscillations on the local temperature and precipitation over the United Arab Emirates (UAE), which is one of the driest regions in the world with very high temperatures and low precipitation. The identification and assessment of remote interactions (teleconnections) are carried out by using ground station and gridded data sets. Monthly rainfall data from six ground stations over the UAE for the period of 1982–2010 is used in this study along with the long-term gridded precipitation and temperature data from the Global Precipitation Climatology Center and Global Historic Climatic Network. Linear correlations, wavelet analysis, and cross-wavelet analysis have been applied to identify the relation between climate indices and precipitation (temperature). The analysis reveals that the strong variability in precipitation is closely associated with the Southern Oscillation Index (SOI) and the Indian Ocean Dipole Index (IOD) during the months of August–March, September–January, respectively. In case of temperature, the strong variability is associated with the North Atlantic Oscillation Index (NAO) and the East Atlantic Oscillation Index (EAO) during the months of April–October, July–December. Spatial analysis of cross-wavelet reveals that the winter precipitation is significantly influenced by SOI and temperature during summer by the NAO. This research concludes that the negative phases of SOI (NAO) play a significant role in the increase of precipitation (decrease in summer temperatures) over the UAE region.

Description: ABSTRACT Interannual variability and long-term changes of summer temperature extremes and hot spells in Moscow during 1949–2012 are investigated using air temperature station data, the National Centres for Environmental Prediction/the National Centre for Atmospheric Research (NCEP/NCAR) reanalysis and the Climatic Research Unit (CRU) data sets. Significant interdecadal changes in different characteristics of the temperature extremes are revealed. It is shown that summertime warming detected in the Moscow region in recent decades is not solely due to an increase in the number of hot days, but also due to a decrease in the number of cold days. Statistically significant positive (negative) trends in the number of anomalously hot (cold) days since the mid 1970s are detected. Respective trend values are 5%/decade –1 for the positive trends and −6%/decade –1 for the negative trends. We find that in 1981–2012 the number of summer seasons with extremely hot days has doubled with respect to earlier period (1949–1980). However, we do not find statistically significant trend-like changes in the duration of the hot events in Moscow. A chronology of temperature extremes in Moscow has been constructed. This can be used as a diagnostic tool allowing the detection of extremes. Typical regional sea level pressure patterns associated with air temperature extremes in Moscow are defined and briefly described.

Description: ABSTRACT This study evaluates the capability of regional climate models (RCMs) in simulating extreme rainfall events over Southern Africa, and in reproducing the characteristics of widespread extreme rainfall events (WERE) in the Western Cape (South Africa). We obtained simulation datasets of nine RCMs from the Co-ordinated Regional Downscaling Experiment (CORDEX) and compared them with observation datasets from the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) as well as with the reanalysis dataset (ERAINT) that forced the simulations. A self-organising map was used to classify the WEREs into 12 nodes. The contribution of each RCM to each node was compared with the contributions of GPCP, TRMM and ERAINT. Using ERAINT dataset, we analysed the synoptic-scale atmospheric condition associated with each node. The results show that, in simulating the spatial distribution of the extreme rainfall event over Southern Africa, only four RCMs perform better than the forcing reanalysis (ERAINT) while two RCMs perform worse than the reanalysis. All the RCMs underestimate the threshold of extreme rainfall over Western Cape, poorly simulate the inter-annual variability of the WEREs ( r ≤ 0.3), but correctly reproduce the maximum frequency of the WEREs in Autumn (March–May). The WEREs in the Western Cape may be broadly grouped into four synoptic rainfall patterns. The first pattern links WEREs with tropical rainfall activities (tropical-temperate troughs); the second pattern shows isolated WEREs; the third and fourth patterns link WEREs with rainfall activities in the mid-latitudes (frontal systems) and over the Agulhas Current, respectively. While most RCMs overestimate the frequency of the first pattern, they all underestimate the frequency of the second pattern but simulate the frequencies of the third and fourth patterns well. The results of this study should help in improving the RCM simulations over Southern Africa and in downscaling impacts of climate change on extreme rainfall events over the region.

Description: ABSTRACT The research objectives were to describe heat waves (HWs) in Central Europe and define the synoptic situations that cause their occurrence. In this article, a hot day was defined as a day when the maximum temperature was above the 95th annual percentile and an HW was considered a sequence of at least five hot days. In the analysed multi-year period and study area, 11 HWs were observed in the north and 51 HWs were observed in the south. The occurrence of HWs was mainly connected with positive anomalies of sea level pressure and with the 500 hPa level, which shows the presence of high-pressure systems. HWs were also accompanied by positive T850 and precipitable water (PW) anomalies.

Description: ABSTRACT A statistical-dynamical downscaling method is used to estimate future changes of wind energy output ( Eout ) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

Description: ABSTRACT Atmospheric teleconnections have an important influence on the variability of the Mediterranean climate. This region has a unique and sensitive climate due to its complex topography and atmospheric circulation, thus making it challenging in climate simulations. This article focuses on the representation of five teleconnections in and around the Mediterranean region and how they affect one another and the region. The Regional Climate Model, RegCM4, has been used to simulate the climate from 1969 to 1999 for a domain covering the Mediterranean and the surrounding region. A generalized method for calculating the indices for these patterns was identified and the corresponding indices were constructed from the modelled data and compared with reanalysis data. The modelled data was found to be highly correlated with the 20th Century Reanalysis data and the probability density functions (PDFs) were very similar to the reanalysis data, showing that the teleconnections were successfully represented within the model. Maps of the influence of these teleconnections on temperature, precipitation and wind were also comparable to the reanalysis data, thereby suggesting that model data can be used for future projections of teleconnections and their effects on these parameters. With the use of this high-resolution data, inter-pattern relationships suggested in previous studies (such as that between the Mediterranean Oscillation and North sea-Caspian Pattern) became more evident. This article also shows how the influence of teleconnections on winds affects the circulation and hence the temperature and precipitation of the region.

Description: ABSTRACT The Mediterranean coast of Spain often experiences intense rainfall, sometimes reaching remarkable amounts of more than 400 mm in one day. The aim of this work is to study possible changes of extreme precipitation in Spain for this century, simulated from several Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Eighteen climate projections (nine models under RCP4.5 and nine RCP8.5 scenarios) were downscaled using a two-step analogue/regression statistical method. We have selected 144 rain gauges as the rainiest of a network by using a threshold of 250 mm in one day for a return period of 100 years. Observed time-series have been extended using the ERA40 reanalysis and have subsequently been used to correct the climate projections according to a parametric quantile–quantile method. Five theoretical distributions (Gamma, Weibull, Classical Gumbel, Reversed Gumbel and Log-logistic) have been used to fit the empirical cumulative functions (entire curves, not only the upper tail) and to estimate the expected precipitation according to several return periods: 10, 20, 50 and 100 years. Results in the projected changes for 2051–2100 compared to 1951–2000 are similar (in terms of sign and value) for the four return periods. The analysed climate projections show that changes in extreme rainfall patterns will be generally less than the natural variability. However, possible changes are detected in some regions: decreases are expected in a few kilometres inland, but with a possible increase in the coastline of southern Valencia and northern Alicante, where the most extreme rainfall was recorded. These results should be interpreted with caution because of the limited number of climate projections; anyway, this work shows that the developed methodology is useful for studying extreme rainfall under several climate scenarios.

Description: ABSTRACT Air temperatures have increased globally over the past decades, while rainfall changes have been more variable, but are taking place. In South Africa, substantial climate-related impacts are predicted, and protected area management agencies will need to respond actively to impacts. It is critical for management agencies to understand the way in which climate is changing locally to predict impacts and respond appropriately. Here, for the first time, we quantify observable changes in temperature and rainfall in South African national parks over the past five to ten decades. Our results show significant increases in temperatures in most parks, with increases being most rapid in the arid regions of the country. Increases in the frequency of extreme high temperature events were also most pronounced in these regions. These results are consistent with other climate studies conducted in these areas. Similar increases were identified for both minimum and maximum temperatures, though absolute minimum temperatures increased at greater rates than absolute maxima. Overall, rainfall trends were less obvious, but a decrease in rainfall was observed for the southern Cape (in three parks), and an increase was detected in one park. The observed temperature changes over the last 20–50 years have in several instances already reached those predicted for near future scenarios (2035), indicating that change scenarios are conservative. These results provide individual parks with evidence-based direction for managing impacts under current and projected changes in local climate. They also provide the management agency with sub-regional information to tailor policy and impact monitoring. Importantly, our results highlight the critical role that individual weather stations play in informing local land management and the concerns for parks that have no local information on changes in climate.

Description: ABSTRACT Desertification is an international environmental challenge which poses a risk to portions of over 100 countries. Research into desertification and climate change has the potential to contribute to natural resources management and adaptation to climatic and other changes in Earth systems. An Earth system model of intermediate complexity (EMIC), the McGill Paleoclimate Model-2 (MPM-2) was used to explore the climatic biogeophysical effects of desertification in different latitude bands from 1700 to 2000 AD. It was found that latitudinal-band desertification attributable to forest and grass removal caused global cooling, land surface albedo increasing and precipitation reduction in the Northern Hemisphere as well as heat transport increasing in global ocean. These results highlighted global climate reaction to local desertification and demonstrated that the location of the desertification projected a potentially differential impact on local and global climate. That was, desertification in 0°–15°N gave a somewhat minor effect on global and local climate; desertification in 45°–60°N caused a significant reduction in global temperature while desertification in 15°–30°N induced a prominent reduction in local temperature. In response to desertification, surface albedo change as a forcing was the dominant biogeophysical driver of climate over the Northern Hemisphere while precipitation change as a response was probably the primary driver of climate over the Southern Hemisphere. Overall, the regional desertification may cause a global climatic effect, especially concerning desert expansion along the 15°–30°N and 45°–60°N latitude bands, which led to a more prominent effect on the Earth's climate and even oceanic circulation. The results of this study provide useful information when comparing the effects of desertification in different latitude bands on climate.

Description: ABSTRACT The spatial structure and temporal evolution of the intraseasonal variability (ISV) of the subsurface ocean temperature (STA) in the equatorial Pacific associated with the two flavours of El Niño [i.e. the canonical or eastern Pacific (EP) El Niño and the central Pacific (CP) El Niño] are investigated using observations and 1.5-layer linear reduced gravity model. Results suggest that the ISV characteristics show some differences in the two types of El Niño, although both oscillate along the thermocline in the form of the intraseasonal equatorial Kelvin wave (IEKW), which is excited in the western tropical Pacific by the zonal wind stress associated with the Madden–Julian oscillation (MJO). First, the period of dominant mode of the STA ISV during CP El Niño broadly distributes in 50–80 days with the spectra peaking in 60–65 days. By contrast, the spectrum of STA ISV during EP El Niño shows a peak in 75–80-day period. This indicates that the wave speed is faster in the CP El Niño than in EP El Niño. Second, the ISV activity peaks in previous spring during the developing phase of EP El Niño, whereas during CP El Niño it becomes the most active during the mature phase. Third, the strongest IEKW occurs in the CP around the dateline during CP El Niño and attenuates quickly east of 130°W due to strong eddy viscosity dissipation, while the IEKW during the EP El Niño propagates efficiently from the western to the eastern Pacific with a relative weak diffusion.

Description: ABSTRACT Mount Kenya is an equatorial mountain whose climatic setting is fairly simple (two rainy seasons in March–May, the Long Rains, and October–December, the Short Rains) though concealing significant spatial variations related to elevation and aspect (part I, Camberlin et al. , 2014). This part II is dedicated to the sensitivity of sorghum yields to climate variability in space and time, with a focus on the intra-seasonal characteristics of the rainy seasons. To that aim we use the crop model SARRA-H calibrated for the region and fed with rainfall, temperature, wind speed, humidity and solar radiation data over the period 1973–2001 at three stations located on the eastern slopes of Mount Kenya. The crop model is run independently for the two rainy seasons. Four groups of simulations are conducted by varying the initialization date of the simulation, the sowing dates and the type of soil, in order to test sorghum sensitivity to water availability. Evidence is found that potential sorghum yields are dominantly controlled by variations in seasonal rainfall amounts: mean yields are higher at higher and wetter locations, and are higher during the wettest rainy season and years. However, beyond this apparent simplicity, more complex aspects emerge of the crop–climate relationships. First, the yield–elevation relationship is altered at high elevation due to lower temperature. Second, despite a strong link with the seasonal rainfall amounts, we evidence an underlying role of some intra-seasonal rainfall characteristics such as the number of rainy days (itself mainly determined by the rainy season duration) or the occurrence of long dry spells. Third, unseasonal rains occurring after the end of the rainy season, especially after the Short Rains, play a role in final crop yield. Fourth, variations of climate variables such as solar radiation by modulating the potential evapotranspiration concur to yield variations at the wettest locations.

Description: ABSTRACT Climate variability modulates spatio-temporal variability of dry spells (DSs) and wet spells (WSs) within a river basin and will affect water resources management practices leading to various impacts on the socio-economic development in river basins. In this study, we evaluated spatio-temporal variability of DS and WS in Huai River basin (HRB), China, by developing copula-based severity-duration-frequency (SDF) curves. The result shows that the upper reach and the southern part of middle reach of HRB are prone to both DS and WS; however, the duration and severity of WS are comparatively higher in comparison to DS. It was observed that DS is more frequent in spring and summer, whereas WS in summer and autumn. The choice of copula plays an important role in deriving the SDF curves, and an inappropriately chosen copula function may result in a large bias of SDF estimation. The arch12 copula was found to be the best choice in the majority of stations for deriving the SDF curves. The constructed SDF curves primarily shows two major patterns for DS and WS, i.e. concave down pattern and convex up pattern. The frequency of extreme DS decreases from 1960s to 1990s, and increases after 2000s, while the frequency of extreme WS increases from 1970s to 1990s and then decreases from 1990s to 2000s. The results in this study can provide useful information for designing conservation structures and to develop water allocation strategies at different temporal scales.

Description: ABSTRACT Careful planning of the use of water resources is critical in the semi-arid eastern Mediterranean region. The relevant areas are characterized by complex terrain and coastlines, and exhibit large spatial variability in seasonal precipitation. Global seasonal forecasts provide only partial information of the precipitation as a result of their coarse spatial resolution. We present two statistical downscaling methods of global forecasts, both identifying past-analogue synoptic-weather patterns and their connection to precipitation at specific stations. The first method utilizes a classification of the large-scale weather patterns into regimes, and the other identifies the closest past analogues directly without grouping the weather events. The validation of the algorithms using NCEP/NCAR reanalyses and past precipitation observations at 18 stations shows that both methods provide good skill in predicting mean precipitation amounts and quantiles of the precipitation distribution, and in reproducing the observed inter-annual and spatial variability. Both methods show good correlations between predicted and observed precipitation amounts (∼0.8), and the downscaled precipitation reproduces the observed differences between the stations, which are not available in the coarse global models. Based on these results, we downscaled the operational global-seasonal forecasts issued by the NCEP CFS1.0 ensemble. This approach could also have utility in climate change scenario downscaling.

Description: ABSTRACT Small Island Developing States in the tropical western Pacific are among the most vulnerable to climate change. While a great deal of information on the observed climate change trends and their cause is available for many other regions and for the globe as a whole, much less information has been available specifically for the Pacific. Here, we show that warming over the past 50 years in the western Pacific is evident in recently homogenized tropical station data, and in gridded surface temperature data sets for the region. The warming has already emerged from the background climate variability. The observational data and Coupled Model Intercomparison Project Phase 5 climate model output are used to show that the observed warming was primarily caused by human-forced changes to the earth's radiative balance. Further warming is projected to occur in the same models under all three Representative Concentration Pathways (RCPs) considered (RCP2.6, RCP4.5 and RCP8.5), with the magnitude far exceeding the warming to date under the two scenarios with higher emissions (RCP4.5 and RCP8.5).

Description: ABSTRACT The contribution by tropical cyclones (TCs) to extreme rainfall in Australia is examined using daily rainfall measurements from over 2000 rain gauges. Analyses focus on the period beginning with regular satellite monitoring of TCs (1969/1970) through the year 2012/2013 and consider daily and multi-daily annual maximum rainfall series. Our results indicate that TCs play a prominent role in extreme rainfall over much Australia, with more than half of the highest annual rainfall events associated with these storms over the coastal regions and in particular over Western Australia. Moreover, the TC fractional contribution to extreme rainfall increases as we focus on the largest rainfall events, with approximately 66–100% of annual maxima in excess of 100 mm (∼4 inches) over Western Australia associated with TCs at over one third of the locations. Given the well-established controls on Australian TC activity by the El Niño–Southern Oscillation (ENSO), we also examined the relationship between extreme rainfall associated with TCs and ENSO using logistic regression. A larger probability of having an annual rainfall maximum related to TCs occurs during La Niña years, consistent with enhanced Australian cyclogenesis during these phases of ENSO. We also highlighted regional differences in the link between ENSO and extreme rainfall events, highlighting the stronger connection along the coastal areas and in particular over Western Australia.

Description: ABSTRACT In the study, the clear-sky aerosol radiative effects have been quantified at 52 European sites using empirical and radiative transfer modelling approaches. Furthermore, the trends of the aerosol radiative effects are also determined for the period of 2001–2012. The aerosol radiative effects are simulated using the Mesoscale Atmospheric Global Irradiance Code radiation code with aerosol and water vapour climatology. The annual mean of the surface aerosol radiative effects in clear-sky situations over Europe is −7.1 ± 2.9 W m −2 . The trends of the aerosol radiative effects are derived assigning radiative effects to monthly Moderate Resolution Imaging Spectroradiometer aerosol optical depth time series applying linear fitting. In the indirect approach, the clear-sky situations are selected from daily surface solar radiation observations from the Word Radiation Data Centre, and the trends of the aerosol radiative effects are delimitated in these clear-sky radiation time series. The two approaches give good fit, based on the direct approach the annual trend of the aerosol radiative effects on clear-sky solar surface radiation is −4.41 W m −2 per decade for the period of 2001–2013, while in the case of the indirect approach, this trend is found to be −4.46 W m −2 per decade. The seasonal trends of the aerosol radiative effects vary between −7.57 and −0.17 W m −2 per decade indicating stronger decreases in summertime. The results are presented for four sub-regions of Europe detecting negative changes in all cases with a stronger decrease in the central, north-eastern and southern part of the continent. The trends of the aerosol radiative effect have the same magnitude as the trends detected in clear-sky solar surface radiation, and are an order of magnitude higher than the radiative effects of water vapour (0.20 W m −2 per decade).

Description: ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983–2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days (TX10p) and cools nights (TN10p) had decreased whereas warm days (TX90p) and warm nights (TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum (TXmean) and minimum temperature (TNmean) had increased significantly by 0.18 and 0.30 °C decade −1 , respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity (SDII) had increased significantly over the country by 0.21 mm day −1  decade −1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount (RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December–January–February (DJF) and/or March–April–May (MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June–July–August (JJA), September–October–November (SON) and MAM.

Description: ABSTRACT Based on the daily rainfall data since 1889 in Curitiba, one of the largest cities in southern Brazil, a trend towards increased precipitation and more intense rainfall can be seen. The annual and seasonal volume of rainfall has increased, amounts greater than 10, 20 and 40 mm being observed more often, but with a reduction in the number of rainy days and the number of days with rainfall below 10 mm. Seasonal 95th percentile series have increased in summer, fall and winter. In addition, several indices of climate extremes presented significant increasing trends: monthly maximum 1-day precipitation, annual total precipitation greater than 95th and 99th percentiles, number of consecutive dry days and the daily intensity index. Generalized extreme value (GEV) distribution function parameters also indicated higher occurrence of extremes detected by the increase in both the scale parameter σ and the location parameter μ in summer, fall and winter. The return time for severe rainfall declined in the second half of the period compared to the first, indicating more frequent occurrence of future extreme events. The main climate indices affecting the 95th percentile series were sea surface temperature (SST), South Atlantic Convergence Zone (SACZ) and Southern Oscillation Index (SOI) during spring, and Atlantic Multi-decadal Oscillation (AMO), Large-Scale Index for South America Monsoon (LISAM) and SOI during the summer, which explained variability of the extremes at around 20 and 13%, respectively in each season. Regarding the variability of summer, fall and spring total rainfall, they presented values around 20% for the explained variance due to climate indices. Other factors should be investigated to explain the variability such as urbanization, air pollution and local circulations. Dominant oscillation periods in the time series constructed with one monthly extreme appeared at 3 to 8-year (inter-annual) cycles, with 12 years (decadal) and around 30–64 years on the inter-decadal scale. These oscillations have resonance with SOI, SACZ and Southern Annular Mode (SAM) indices (high frequencies), and Pacific Decadal Oscillation (PDO) and AMO (low frequency).

Description: ABSTRACT Climate change affects mean and extreme temperature and precipitation, increasing the risk of related disasters. Assessing the performance of current models in simulating these aspects is therefore crucial to future projection and policymaking. Based on a large ensemble (LE; 30 members) of the Community Earth System Model (CESM-LE), this study seeks to answer the following two questions: (1) Are the simulated trends of mean and extreme temperature and precipitation over China consistent with observations? (2) What is the range of model uncertainty due to internal variability? The results show that CESM-LE can capture the trends of observed annul mean temperature and extremely low temperature days (ELD) over 16–26% of China, but has difficulty in reproducing the observed trends in extremely high temperature days (EHD). For precipitation, CESM-LE demonstrates similar capability in reproducing the observed trends in annual mean precipitation and extreme precipitation days (EPD). For consecutive dry days (CDD), the decreasing trends over part of northwestern China can be captured, but the increasing trends over northern China cannot be reproduced by CESM-LE. Regarding the uncertainty of the model resulting from natural internal variability, because all 30 ensemble members of CESM use the same model and external forcing, CESM-LE's spread (uncertainty) is mainly due to internal variability. Larger uncertainty in simulated trends is found over northern China and the Tibetan Plateau for annual mean temperature, over northeastern China and the Huang-Huai region for ELD, and over the Tibetan Plateau for EHD. The trends in annual mean precipitation show uniform uncertainty over nearly all of China, except for the northwest. Larger uncertainty trends appear over southern and northwestern China for EPD, and over the Tibetan Plateau and northern China for CDD.

Description: ABSTRACT This study presents the spatio-temporal winter snow albedo analysis over different mountain ranges of north-west Himalaya (NWH) for a period of approximately 24 years. Here we assess the temporal albedo variations in past two decades (1991–2010) in comparison to the recent 14 years (2000–2014). The field collected manual data of two representative observatories of Lower Himalaya (LH) and Great Himalaya (GH), and six automatic weather stations in LH, GH and Karakoram Himalaya (KH) were analysed. Satellite derived MODIS albedo data (MOD10A1) over these stations between 2001 and 2014 were analysed. A good correlation ( r  = 0.59) was observed between monthly average MODIS retrieved albedo and field collected albedo for GH with a relative error of 11%. In past two decades, a statistically significant (99%) decreasing rate of −0.011 per year in winter snow albedo was observed over GH (1993–2010), while in recent decade (2001 onward), no statistically significant increasing trend was observed. The change in albedo of GH is attributed to winter mean air temperature, which shows a significant rise in the past two decades, but there has been a hiatus in winter mean air temperature rise in recent decade. The higher winter mean air temperature above 0 °C since beginning of the study period (1991 onward) kept albedo of moist/wet snow approximately stable in LH. Further, insignificant increasing trend of albedo was observed over KH range in recent decade, and it is attributed to persistent very low temperatures and an increase in the frequency of snowfall days. This albedo study over NWH supports the recently reported findings on Himalayan snow cover and glacier variations during different durations.

Description: ABSTRACT Recent projections of climate change from general circulation and regional climate models over southern Europe and the Mediterranean basin show strong warming and pronounced decrease in precipitation over large portion of the region, especially in the summer. While the role of vegetation in modulating the region's climate is widely recognized, most, if not all, of these climate change projections do not account for the response of the dynamic biosphere to the potential climate changes. In this study we investigate the role of climate–vegetation interactions in a regional climate model (RegCM3) linked to a dynamic vegetation model (CLM-DGVM). High spatial resolution (20 km) simulations of future climate with static vegetation (i.e. vegetation fixed at the present day state) show surface temperature increases across the entire southern Europe/Mediterranean domain in 2085–2089 relative to 1985–1989 due to the radiative and physiological effects of CO 2 increase. In terms of precipitation the simulations exhibit substantial precipitation decreases for most of the domain and both summer and winter seasons. Accounting for the effects of structural vegetation changes significantly alters the simulated climate change effects over these areas, but most substantially over the Mediterranean where vegetation feedback reduces summer warming by 1 K and reverts the 28% precipitation decrease to a 4% increase. These results emphasize the importance of including vegetation feedback in the projections of climate change impacts on the Mediterranean climate including extreme climatic events and storms.

Description: ABSTRACT Vegetation types are generally classified based only on remote sensing vegetation data, and yet they cannot reflect their connection with climate. Climatic vegetation types reflect the regional vegetation characteristics in terms of climate. The distribution of global climatic vegetation types were identified by K-means method based on vegetation and climate data. Fourteen climatic vegetation types were classified based on vegetation and climate data. Every type had distinct climate and vegetation characteristics. The regions with similar normalized difference vegetation index (NDVI) values but with different climate values such as tropical desert and temperate desert could be distinguished. Our new updated climatic vegetation types agreed ‘fair’ with Koeppen climate types and climate type of Zhang and Yan while agreed ‘good’ with vegetation types when checked with Kappa test.

Description: ABSTRACT A detailed understanding of past temporal patterns and spatial expression of temperature variations is important to place recent anthropogenic climate change into a longer term context. In order to fill the current gap in our understanding of northwest European temperature variability, point-by-point principal component regression was used to reconstruct a spatial field of 0.5° temperature grids across Scotland. A sequence of reconstructions utilizing several combinations of detrending and disturbance correction procedures, and a selection of tree-ring parameters [including ring width (RW), maximum latewood density (MXD) and blue intensity (BI)] was used in an evaluation of reconstruction skill. The high resolution of the reconstructed field serves also as a diagnostic tool to spatially assess the temperature reconstruction potential of local chronologies. Best reconstruction results, reaching calibration r 2  = 65.8% and verification r 2  = 63.7% in central Scotland over the 1901–1976 period, were achieved using disturbance-corrected and signal-free detrended RW chronologies merged with BI data after low-pass (high-pass) filtering the RW (BI) chronologies. Calibration and verification r 2  〉 50% was attained for central, north and east Scotland, 〉40% in west and northwest, and 〉30% in southern Scotland with verification of nearly all grids showing some reconstruction skill. However, the full calibration potential of reconstructions outside central Scotland was reduced either due to residual disturbance trends undetected by the disturbance correction procedure or due to other climatic or non-climatic factors which may have adversely affected the strength of the climate signal.

Description: ABSTRACT Intraseasonal precipitation, wind, and vertically integrated moisture flux variability were assessed from June to August between 1998 and 2009. To that end, we used daily precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim reanalysis. The composites of precipitation anomalies showed that during the intraseasonal enhancement of convective activity over the area assessed, increased precipitation occurs over the northern coast of South America; the opposite is true during the decrease in intraseasonal convective activity. The convective activity over the region of maximum precipitation variance is intraseasonally enhanced during 210 days, whereas the decrease occurs during 194 days. During the days on which the convective activity over the region of maximum precipitation variance was enhanced (decreased) by the Madden–Julian oscillation, the frequency of African easterly waves (AEWs) cases was greater (lower). The most significant average characteristics observed during this period were the displacement of positive precipitation anomalies toward the north and the intensification of the flux toward the tropical North Atlantic Ocean. This pattern disfavours precipitation over the northern coast of South America. On the other hand, during the dry period of Madden–Julian oscillation, there was a decrease in AEWs cases which, although there was negative precipitation anomalies over the northern coast of South America, there were positive anomalies over northwest South America. Therefore, the increase (decrease) in convective activity over the region of maximum precipitation variance favours (disfavours) the frequency of AEWs over this region and, consequently, the precipitation over the northern coast of South America decreases (increases) during the dry season (June to August).

Description: ABSTRACT Previous studies suggest that climate change impacts significantly on the hydro-climatic processes within the Ganges–Brahmaputra–Meghna (GBM) River Basin (RB). This study examines the observed climate characteristics and potential strengths and limitations of three global high-resolution reanalyses and satellite remote-sensing products over the GBM RB for period 1980–2013 by (1) estimating trends and interannual variations of precipitation and temperature, and (2) isolating precipitation variations likely associated with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The surface temperature trends show widespread warming across the basin with a maximum increase of 0.6 °C decade −1 over western Nepal and southern Tibet from 1980 to 2013. Rainfall changes from 1980 to 2013 indicate pronounced decline over high rainfall regions of northeast India, Bhutan, Nepal, and Bangladesh, especially from 1998 to 2013. Basin-wide averaged trends show rainfall decline of up to 39 mm decade −1 in June–August in the Brahmaputra–Meghna RB from 1998 to 2013. Temperature variability based on Principal Component Analysis indicates that the first mode is associated with sea surface temperature (SST) warming in the Arabian Sea and the western tropical Pacific Ocean, while the second mode appears to be significantly correlated to SST anomalies in the western (eastern) tropical Indian (Pacific) Ocean. ENSO and IOD events are found to significantly influence rainfall variability contributing to about 10–20% (ENSO) and 8–10% (IOD) of the annual rainfall, mainly over Bhutan, Nepal, Bangladesh, and north-eastern India. Among the three reanalysis products: European Centre for Medium-Range Weather Forecasts (ECMWF) retrospective analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR), ERA-Interim (and MERRA) agrees well with the observed precipitation (temperature) data sets while, CFSR shows the least skills in representing the spatio-temporal variations of precipitation and temperature.

Description: ABSTRACT This study has investigated the influence of the decadal component of the Pacific Decadal Oscillation (PDO) on the Indian monsoon in observations and coupled climate model. A major part of the conventionally defined PDO is shown to be dominated by interannual variability. By extracting the pure decadal part of the North Pacific variability, this study has shown that the Indian monsoon rainfall exhibits different relations with the conventionally defined PDO and the pure decadal component of the PDO. This result may have implications for decadal prediction of the monsoon. The analysis suggests that the warm (cold) phase of pure decadal variability of PDO is associated with deficit (excess) rainfall over the west central part of India. In contrast, the conventional warm (cold) PDO index is associated with deficit (excess) rainfall over most of India. The warm phase of the pure decadal PDO opposes the moisture flow beyond 20°N over the Indian monsoon region via the meridional winds extending from the North Pacific and leads to reduced rainfall over west central India. The Community Climate System Model version 4 of the National Center for Atmospheric Research shows reasonable simulation of the decadal PDO mode in both the North Pacific sea surface temperature and the Indian monsoon rainfall and the relation between them. Further, the observed and simulated PDO–monsoon relation is substantiated through a regionally de-coupled experiment. The coupled model experiment also provides supporting evidence for the mechanism involving the intermediary role played by the tropical Pacific Ocean in the PDO–monsoon relation.

Description: ABSTRACT This study explores the sensitivity of high-resolution mesoscale simulations of urban heat island (UHI) in the Chicago metropolitan area (CMA) and its environs to urban physical parameterizations, with emphasis on the role of lake breeze. A series of climate downscaling experiments were conducted using the urban-Weather Research and Forecasting (uWRF) model at 1-km horizontal resolution for a relatively warm period with a strong lake breeze. The study employed best available morphological data sets, selection of appropriate urban parameters, and estimates of anthropogenic heating sources for the CMA. Several urban parameterization schemes were then evaluated using these parameter values. The study also examined (1) the impacts of land data assimilation for initialization of the mesoscale model, (2) the role of urbanization on UHI and lake breeze, and (3) the effects of sub-grid scale land-cover variability on urban meteorological predictions. Comparisons of temperature and wind simulations with station observations and Moderate Resolution Imaging Spectroradiometer satellite data in the CMA showed that uWRF, with appropriate selection of urban parameter values, was able to reproduce the measured near-surface temperature and wind speeds reasonably well. In particular, the model was able to capture the observed spatial variation of 2-m near-surface temperatures at night, when the UHI effect was pronounced. Results showed that inclusion of sub-grid scale variability of land-use and initializing models with more accurate land surface data can yield improved simulations of near-surface temperatures and wind speeds, particularly in the context of simulating the extent and spatial heterogeneity of UHI effects.

Description: ABSTRACT The seasonal variation of the atmospheric structure, vertical shear, stability, and rainfall distribution over the island of Kyushu, southern Japan, is studied using 16 years of observational data, from 1998 to 2013. Over 20 000 twice-daily rawinsonde observations from the cities of Kagoshima (southern Kyushu) and Fukuoka (northern Kyushu) are utilized along with daily precipitation data from 120 Japan Meteorological Agency stations located across the island. Understanding the local atmospheric circulation and climatological behaviour of the island is important both locally due to the island's large population and regionally, due to its position in relation to the tracks of typhoons generated annually over the Pacific ocean and make landfall here, the rainy season associated with the Asian monsoon, and the large number of active volcanoes located on or near the island, emitting volcanic gases and ash on a daily basis. Using a categorisation based on convective available potential energy and precipitable water, three sounding categories are distinguished, described using the origins of the air masses involved, as seen from trajectory modelling: continental (dry), oceanic (moist/unstable), and mixed (moist/stable). Mean soundings for each category are examined, along with information on their annual and seasonal variability. Each sounding category is linked with a rainfall response: low amounts of rainfall, heavy convective rainfall, and heavy, non-convective rainfall, respectively. Despite the large difference in the potential for heavy rainfall rates, average daily rainfall rate is similar for the two moist categories, but peak rainfall rates for convective rainfall are twice as large as those for non-convective. Despite the simplicity of the criteria, the three sounding categories are statistically robust and exhibit a relatively small amount of variability. The monthly combination of the sounding categories is shown to be a deciding factor in the seasonal variation of the atmospheric circulation, weather, and precipitation over the island.

Description: ABSTRACT The development of Adapted Caussinus–Mestre Algorithm for homogenising Networks of Temperature series (ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 (HOME) has been continued. The third generation of the software package ‘ACMANT3’ contains six programmes for homogenising temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including for break timing assessment, gap filling and ANOVA application on the daily time scale. Examples of efficiency tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3 can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is included, and some caveats in relation to how and when ACMANT3 should be applied are provided.

Description: ABSTRACT Snow cover extent, duration, and properties were simulated (1979/1980–2013/2014) for the Rio Olivares Basin (548 km 2 ) in central Chilean Andes, in an effort to understand conditions and trends (linear) at a basin scale. The National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications products, together with the snow modelling software package SnowModel allowed simulations of first-order atmospheric forcings (mean annual air temperature (MAAT) and water-equivalent precipitation) and terrestrial snow features (snow cover extent, duration, snow water-equivalent depth, snow density, and runoff generated from snow melt). Simulated snow cover extent and depletion curves were verified against Moderate Resolution Imaging Spectroradiometer-derived snow cover data. For the Rio Olivares Basin, MAAT was −2.9 ± 0.6 °C with a mean 0° isotherm at 3325 m a.s.l. The greatest temporal and spatial changes in temperature over the 35-year period occurred in January and at the highest elevations, respectively. Mean annual precipitation was 1.86 ± 0.60 m w.e., indicating an increase in precipitation of ∼0.1 m w.e. 100 m −1 increase in elevation. On average, ∼90% of the basin precipitation fell as snow, varying from 70% at ∼2600 m a.s.l., to 95% at ∼4200 m a.s.l. In 20 out of 35 years the snow cover extent went to 0% (no basin snow cover) by end-of-summer (during March), and the snow duration increased on average by ∼10 days 100 m −1 increase in elevation. Approximately 85% of the basin outlet freshwater runoff originated from snowmelt, making snowmelt a dominant contributor to water resources. Snowmelt-derived basin runoff was dominated by variability in snow precipitation rather than by variability in MAAT.

Description: ABSTRACT This contribution employs instrumental records to analyse the temporal and spatial variability of monthly, seasonal and annual maximum wind gusts (MWGs) in the Czech Republic. The development of an observation network capable of measuring wind gusts, the possible technical weaknesses of wind measurements and problems with establishing homogeneity in wind-gust data are described. For the 1961–2014 period, quality-checked data from 19 synoptic stations of the Czech Hydrometeorological Institute throughout the territory of the Czech Republic are examined, divided into three altitudinal groups. In terms of the spatial variability of MWGs, correlation coefficients between stations decrease more strongly in relation to station distance rather than altitude. Spatial correlations are better expressed (by higher correlation coefficients) in the winter half-year than in the summer half-year. Linear trends in monthly, seasonal and annual MWGs for the 19 synoptic stations, for their three altitudinal groups, and for the entire Czech Republic show statistically significant decreases (deepest in November and autumn), with the exception of spring (for stations above 300 m) and summer. The 10 highest MWG events of all are selected. The spatial distribution of wind gusts for two prominent windstorms, Kyrill (18–19 January 2007) and Emma (1–2 March 2008), are presented. Changes in MWGs series are compared with fluctuations in atmospheric circulation responding to the North Atlantic Oscillation. Decreasing MWG trends are discussed with respect to diminishing storminess and surface wind speeds (wind stilling) recorded during recent decades in Europe, as well as over other continents.

Description: ABSTRACT This study analyzes the spatiotemporal variability of rainfall and temperature (minimum, maximum and average) trends at 47 stations throughout the Brazilian Legal Amazon for the period 1973–2013. Annual, wet season and dry season trends were quantified by Sen's slope for each station and the entire region. The Mann–Kendall test was used to determine the statistical significance of the trends. For the whole region, minimum, maximum and average annual temperatures showed increasing trend of approximately 0.04 °C per year. The rainfall showed an insignificant trend for most stations for annual and seasonal series. Nevertheless, some stations showed significant increasing trends in the annual and wet season rainfalls while a few stations showed decreasing trends for the dry season rainfall. A positive trend of the annual range between wet and dry season rainfall was found in some stations, caused mainly by an increasing trend in wet season rainfall.

Description: ABSTRACT Quality controlled homogenized regional anomaly series of temperature and precipitation are obtained for the central Pyrenees for the period 1910–2013. A 0.1 °C decade −1 positive trend is found for minimum and maximum annual temperature exceeding the significance level of 0.05 for the whole studied period. A significant warming is found in all seasons except boreal spring in minimum temperature and winter in maximum temperature. The annual regional precipitation anomaly series shows a high inter-annual variability and a slightly negative non-significant trend of −0.6% decade −1 . Non-significant negative trends of precipitation are found in all seasons for the whole period examined. Considering the recent period 1970–2013, values of temperature trends are generally higher than those obtained for the whole period. For this latest period, all maximum temperature trends are significant while only the minimum temperature trend in winter is non-significant. Spring is the season that presents the greatest warming, with 0.9 °C decade −1 for maximum temperature and 0.4 °C decade −1 for minimum temperature. Evaluating the same period for precipitation anomalies, trends in the annual, winter and summer series remain negative, while spring and autumn trends are positive although non-significant. This series represents the longest homogenized climate data set available for the central Pyrenees region, including the newly recovered period 1910–1949, offering new possibilities for climate analysis and paleoclimate proxy calibration.

Description: ABSTRACT A marked seasonality in the occurrence of Madden–Julian Oscillation (MJO) events is well known. The core region of oscillation is located at low latitudes (between the equator and 15°) in the summer hemisphere. The eastward progression of MJO signal interacts with the monsoon circulation and modulates the advance period of Indian summer monsoon (ISM). The analyses suggest that the mean advance period of ISM (41 days) is comparable with the life cycle of the MJO (30–60 days). The advance period of ISM has been categorised into normal, fast and slow-advance years to decide the pace of the monsoon during progression of monsoon. During the period 1983–2015, the fastest progress of the monsoon was seen in the year 2013 (fastest advancement in the last 33 years) and slowest progress of monsoon was seen in the year 2002 (most lethargic advancement in the last 33 years). The results of the analyses show that variation in daily MJO-amplitude during fast-advancement years is more as compared with the normal and slow-advancement years. The normal-advancement years mostly occur during MJO phase 1 and phase 2 and fast-advancement years frequently occur during MJO phase 2; however, slow-advancement years are found to occur during MJO phase 5 and phase 6. The MJO phase 2 is the most frequent phase and MJO phase 8 is the least frequent phase during advance of monsoon. However, the highest amplitude is recorded during MJO phase 8. The strong (weak) monsoon current is modulated by strong (weak) MJO phases.

Description: ABSTRACT This study compares the multivariate predictions of daily temperature, temperature range, precipitation, surface wind and solar radiation of a single-model analogue approach with an original multi-model analogy over 12 regions in Europe and Maghreb. Both approaches are based on two-level analogue models where atmospheric predictors are either dynamic or thermodynamic. In the multi-model approach, independent analogue models with predictand-specific predictors are used. In the single-model one, a unique analogue model and its associated set of predictors is applied to all predictands. Testing numerous large-scale predictors, we first identify the best predictor sets for each modelling strategy. Those obtained for the single-model approach are significantly different from those of the predictand-specific models. This is especially the case for local temperature and wind speed. Both methods perform similarly for precipitation, temperature range and radiation. We next assess the ability of both approaches to simulate physically coherent multivariate weather scenarios. With the single-model method, weather scenarios are obtained for each prediction day from observations sampled simultaneously on one analogue day. The physical consistency between variables is thus automatically fulfilled each day. This allows the single-model method to reproduce well the observed inter-predictand correlations, especially the significant correlations between radiation and precipitation and between radiation and temperature range. These results suggest a hybrid analogue model using a single-model for radiation, temperature range and precipitation, combined with a univariate approach for wind. Two options are proposed for temperature for which either the predictand-specific method or a single-model approach with an additional correction are conceivable. This hybrid approach leads to a possible compromise between reasonable univariate prediction skills and realistic inter-predictands correlations, both classically required for many impact studies.

Description: ABSTRACT Southeast Brazil (SE Brazil) is the most densely populated region in Brazil. Previous studies have shown evidence of positive trends in average precipitation and extreme events in a few locations, suggesting the increase in rainfall-related hazards with potential impacts to urbanized areas of SE Brazil. This study provides a comprehensive analysis of the spatial variability of trends in extreme precipitation over SE Brazil focusing on regional and local scales. We examine two daily rainfall datasets with more than 70 years of data: individual stations and gridded observed precipitation data. Our results indicate that the frequency of both rainy days and extreme daily precipitation events have increased in Sao Paulo state. Conversely, precipitation has become more concentrated in fewer events in Rio de Janeiro and Espirito Santo states where both data sets indicate positive trends in the intensity of extreme daily rainfall. The increases in frequency and intensity of extreme events have both contributed to positive trends in total seasonal and average daily precipitation over Sao Paulo. Additionally, the individual stations indicate negative trends in the number of light rainy days over large urbanized areas in the state of Sao Paulo. The spatial patterns of trends indicate that they are influenced by the proximity of large urban centres and topographic features, and also suggest variations and changes in the major climatic systems affecting precipitation regimes over SE.

Description: ABSTRACT Geostationary Operational Environmental Satellite (GOES) visible imagery was used to identify lake-effect (LE) clouds in the North American Great Lakes region for the cold seasons (October–March) of 1997/1998 through 2013/2014 to provide a comprehensive climatological description of the seasonal and interannual variability of LE cloud bands. During the average cold season, at least 60% of days each month had LE clouds over some portion of the Great Lakes region and nearly 75% of all LE days had LE clouds present over several lakes simultaneously. Wind-parallel bands (WPB) are observed far more frequently than any other type of LE over Lakes Superior, Michigan, and Huron during the months of December, January, and February. Over Lake Erie, the occurrence of days per month with WPB was found to be approximately 5–10% greater than days with shore-parallel bands (SPBs) throughout the entire cold season. The greatest frequency of SPB occurrences in the Great Lakes region was over Lake Ontario during the months of January and February (∼20% of days). In addition, Lake Ontario was the only lake where the frequencies of WPB and SPB occurrences were fairly similar each month. The annual frequency of WPB occurrences are the most variable among the Great Lakes, decreasing in frequency from the western lakes toward the eastern lakes. Lake Ontario has the largest annual frequency of SPB occurrences and the greatest variation in SPB annual frequency. Lake Huron has the second largest annual frequency of SPB days with small interannual variation. The primary differences of the annual frequency of lake-to-lake (L2L) LE occurrences when compared with previous research were a greater variability in the L2L annual frequency of Superior-to-Michigan connections, greater frequency of Michigan-to-Huron connections, and less frequent occurrences for Superior-to-Huron and Michigan-to-Erie connections.

Description: ABSTRACT The skill in predicting intraseasonal characteristics of synoptic type occurrences at the seasonal time scale over the all-year rainfall region of South Africa (35°–33°S and 21°–27°E) is assessed by utilizing an ensemble of simulations performed using the GloSea5 coupled ocean–atmosphere model. Hindcasts of daily sea-level pressure fields of 14 austral spring [September–October–November (SON)] and summer [December–January–February (DJF)] seasons, initialized in August and November, respectively, are analysed. The skill assessment is achieved through the use of self-organizing maps. Deterministic and probabilistic assessment of synoptic type frequency forecasts indicate that intraseasonal circulation variability over the Cape south coast region is marginally predictable at seasonal time scales, more so during SON than DJF. In particular, the results obtained demonstrate that there is potential for the skillful seasonal prediction of the anomalous frequency of occurrence of high-impact rainfall events associated with cut-off lows within SON seasons.

Description: ABSTRACT This article specifies a multi-factor long memory process, namely Gegenbauer process, particularly adapted for data with slow damping correlations and cyclical patterns, and explores the use of this representation in the inter-annual climate variability range capture by indices of the El Niño Southern Oscillation (ENSO). The empirical results suggest that sea surface temperature (SST) indices are stationary long memory processes. It is found that the indices in the eastern and central Pacific exhibit different dynamics. The variability of the eastern equatorial Pacific SST indices (Niño 1 − 2 and Niño 3) is characterized by a large component of long-memory behaviour associated with the quasi-biennial and the semi-annual frequency. In contrast, the variability of the central Pacific SST indices (Niño 3.4 and Niño 4) is characterized by a large component of long-memory behaviour associated with the annual and the semi-annual frequency. These results are consistent with recent studies that suggest that ENS0 SST anomalies in the equatorial Pacific can be considered to consist of two processes. The use of Gegenbauer processes can be considered as an alternative competitive procedure in the analysis of cyclical long memory climatological time series from a different time series perspective.

Description: ABSTRACT Lamb's weather types classification has been used here to analyse the characteristics of raindrops in relation with the meteorological situation. A rainfall gathering campaign has been carried out in Leon [northwesterly (NW) Spain] over 34 months. An optical disdrometer has been used to determine drop sizes and the meteorological situations have been classified from the pressure values at surface level in 16 grid points over the study zone. The results have revealed seasonal differences in the average duration of the rain events: 40 min in winter and 12 in summer. In the study period, the rainiest weather types were the cyclonic types, and the air flows from the north and the west. The raindrop sizes follow a gamma distribution with a higher mode in the case of the weather types with air masses from the west and the southwest. The only exception lies in the purely directional weather types, where a higher mode is found in the case of rain events with eastern flows.

Description: ABSTRACT The scientific debate on the impact of climate change on hurricane intensity/strength continues. Regardless of its causes, the consequence of increasing hurricane intensity is undeniably immense among coastal residents. In this study, we investigate how various objective measures of hurricane strength affect people's perception of changing hurricane strength over time. We utilize original survey data to examine the relationship between perceived and actual shift in hurricane strength. In this article, hurricane strength is indicated as maximum wind speed at landfall, storm surge, and economic damage. We find that the characteristics of hurricane strength associated with the most recent landfall are much more closely associated with perceptions of changing hurricane strength than objectively measured trends. This result is consistent with availability bias, suggesting that perceptions are associated with most accessible and retrievable events. We also find that people's belief in climate change play a powerful role in one's perception of changing hurricane strength. Political predispositions are found to affect one's perceptions of changing hurricane strength. Compared to Democrats and Independents, Republicans are far less likely to believe that climate is changing and thus they tend to not believe that hurricanes are becoming stronger. Given that this study focuses on how physical characteristics of past hurricane events influence individual perceptions of hurricane strength shift, future research should focus on how expectations of future climate and weather-related events influence individual attitudes and behaviours.

Description: ABSTRACT The response of field-grown vegetables to adverse weather conditions is strongly coupled to the timing of adverse events, the sensitivity of the growth stage of the impacted crop and the management actions that are taken. To estimate the long-term yield response to changes in temperature and precipitation as well as the short-term response to key adverse weather events (e.g. heavy precipitation, drought and heat stress) on the yields of vegetable crops, we used several statistical approaches with six daily impact-indicators, the four monthly drought indices and the climate trends. Our study integrated a newly available historical yield dataset at the district level (the finest spatial resolution) for all highly marketable vegetables (celeriac, late carrots, root parsley, early kohlrabi, summer savoy cabbage, late cauliflower, late cabbage, onions, green peas, tomatoes, salad and pickling cucumbers) and a high-resolution historical climate dataset (seven daily meteorological variables at a 10 × 10 km resolution) over a 54-year period in the Czech Republic (CZ). Different indices were used to reflect different dimensions of water and heat stress, which have different impacts on vegetable growth and yield. We find positive long-term impacts of recent warming on fruiting vegetables (from 4.9 to 12.2% °C −1 ) but decreases in the yield stability of traditionally grown root vegetables in the warmest areas of the country. Short-term extreme temperature variabilities (days with heat stress) were found to be the dominant type of adverse event for tomato and cucumber production due to its effect on increased soil water demand, which increased transpiration rates, whereas changes in both the diurnal temperature ranges and minimum temperature ( T min) were associated with minimal risk of frost damage. Brassicas vegetables are widely irrigated in the CZ, but irrigation does not fully mitigate drought effects; hence, short-term extreme precipitation variability largely controls crop production in the growing districts. The high frequencies of dry days and days with heavy precipitation within the critical growth stages of brassicas reflect a competition between more dry days and greater precipitation intensity on wet days. The yield variability of bulbs is largely explained by both short-term extreme precipitation and temperature variability (drought-heat stress), which reflects the predominantly rain-fed system of onion cultivation. Both drought and heat stress and changes in T min were important in explaining yield losses of root vegetables. Legumes had the lowest risk of multiple stresses during their short growth cycle, but droughts remain the dominant type of adverse event. Years with yield gains were substantially more common than years with yield losses for brassicas, bulbs and legumes vegetables in all of the cultivated regions.

Description: ABSTRACT As the recent global warming hiatus has attracted worldwide attention, we examined the robustness of the warming hiatus in China and the related dynamical mechanisms in this study. Based on the results confirmed by the multiple data and trend analysis methods, we found that the annual mean temperature in China had a cooling trend during the recent global warming hiatus period, which suggested a robust warming hiatus in China. The warming hiatus in China was dominated by the cooling trend in the cold season, which was mainly induced by the more frequent and enhanced extreme-cold events. By examining the variability of the temperature over different time scales, we found the recent warming hiatus was mainly associated with a downward change of decadal variability, which counteracted the background warming trend. Decadal variability was also much greater in the cold season than in the warm season, and also contributed the most to the previous accelerated warming. We found that the previous accelerated warming and the recent warming hiatus, and the decadal variability of temperature in China were connected to changes in atmospheric circulation. There were opposite circulation changes during these two periods. The westerly winds from the low to the high troposphere over the north of China all enhanced during the previous accelerated warming period, while it weakened during the recent hiatus. The enhanced westerly winds suppressed the invasion of cold air from the Arctic and vice versa. Less frequent atmospheric blocking during the accelerated warming period and more frequent blocking during the recent warming hiatus confirmed this hypothesis. Furthermore, variation in the Siberian High and East Asian winter monsoon season supports the given conclusions.

Description: ABSTRACT To quantitatively describe the Late Holocene palaeoclimatic history of the southern slopes of the Tianshan Mountains in Xinjiang, China, we collected 74 surface pollen samples (from −154 to 4285 m), together with 81 fossil samples from Swan Lake. Based on modern pollen assemblage and redundancy analysis (RDA) of surface pollen data, five pollen zones were divided (alpine cushion vegetation, alpine meadow, subalpine meadow steppe, montane desert, and typical desert zones). Modern pollen–climate transfer functions were developed to quantitatively reconstruct palaeoclimate of the area using the weighted averaging partial least squares regression method. Reconstructed mean annual precipitation and mean annual temperature results suggest that a dry/warm or humid/cold climate pattern prevailed over the past 4200 aBP. Notably, three cold and humid stages were detected at 4200–4000 cal. aBP, 3700–2000 cal. aBP, and 1170–930 cal. aBP. Moreover, a humid ‘Medieval Warm Period’ (MWP) occurred not only on the northern slopes but also on the southern slopes of the Tianshan Mountains. However, based on palaeo-environmental records and on archaeological documents, it would appear that a dry MWP occurred in southern parts of south Xinjiang, with this being different from the MWP on the Tianshan Mountains. Interactions between monsoon and the westerly airflows might account for this difference. The data will improve understanding of past atmospheric circulation systems in the different parts of Xinjiang and will help to predict the future climate in the world.

Description: ABSTRACT In order to clearly classify El Niño–Southern Oscillation (ENSO) events into eastern Pacific (EP) and central Pacific (CP) types, we develop two new indices defined as pattern correlation coefficients (PCCs) between monthly sea surface temperature (SST) anomalies (SSTAs) and first two leading empirical orthogonal function modes of tropical Pacific (20°S–20°N, 110°E–70°W) SSTAs. These new indices not only show close relationships with ENSO indices derived from several previous methods, but also demonstrate reasonable abilities to distinguish between two types of ENSO event. The major characteristic features of the EP-type and CP-type ENSO forcings are well captured from SST responses regressed onto each new index. Furthermore, the monthly frequencies of occurrences derived from two indices are quite similar to variation patterns of phase-locking behaviours of two types of ENSO event.

Description: ABSTRACT An impact of global warming on the first-flowering date (FFD) of cherry, peach and pear in north-eastern Asia are investigated using the Korean national scenario. For the study, we used the dynamically downscaled daily temperature with 12.5 km horizontal resolution derived from five regional climate models (RCMs) under the same lateral forcing from HadGEM2-AO on the basis of Historical (1981–2010) and four Representative Concentration Pathway (RCP) (2021–2100) scenarios. According to our analysis of the Historical simulations, the five RCMs and phenological model have good capability in simulating temperature and FFD with uncertainties of about 2.4–3.4 °C and 8.4–13.9 days, respectively, while well reflecting the topographical effect. On the basis of the highest emission scenario (RCP8.5), the temperature increments of 4.8 °C induce an acceleration in blooming rate, thereby advancing the FFDs of cherry, peach and pear by the end of the 21st century by about 14.5, 15.8 and 14.5 days, respectively, compared with the current reference simulation (Historical). We found high availability of the Korean national scenarios with moderate reliability. We believe that the next generation of the Korean national downscaling project considering diverse lateral forcing will offer better performance and more useful projections to end users.

Description: ABSTRACT This study investigated the climatic influence on the corn sowing date in the Midwestern United States by comparing the survey data of corn cultivation with meteorological records in nine states for the last 36 years (1979–2014). The results show that the year-to-year changes in the sowing date were significantly affected by springtime air temperature and precipitation in the nine states, although large state-to-state differences were found in the degree of sowing date–meteorology relationship. We determined that the 36-year climatological warm period (CWP) with daily mean temperatures ≥10 °C plays an important role in the state-to-state differences. For the states with longer CWPs, the influence of air temperature (precipitation) was generally weaker (stronger). This observed counteractive relationship should be considered for crop modelling for more effective assessment of the impact of climate change on agriculture. Copyright © 2016 John Wiley & Sons, Ltd.

Description: ABSTRACT In this article, we investigate indicators for lightning activity by analysing the data of surface heat flux, Bowen ratio (ratio of sensible to latent heats) and cloud base height for a period of 16 years (1998–2013) over Indo-Gangetic Plain (IGP) (25°–27°N, 80°–88°E), Indian land excluding IGP (8°–36°N, 68°–98°E) and 10 years (2000–2009) over Indian seas [Arabian Sea (5°–20°N, 65°–80°E) + Bay of Bengal (5°–20°N, 80°–98°E)]. Lightning activity varies with the surface heat flux, Bowen ratio and cloud base height over India. Over Indian land, annual lightning flash counts are found to be more by 32 and 24% than those over IGP and Indian seas, respectively. Total heat flux (sensible + latent) and lightning flash counts show a strong correlation coefficient of 0.75 for Indian land and 0.73 for IGP relative to that of Bowen ratio with lightning flash count (0.63 for Indian land and 0.19 for IGP). Hence, the total heat flux represents the best parameter for describing lightning activity over IGP and Indian land. Bowen ratio ≥1 in pre-monsoon increases lightning flash counts over IGP and Indian land. Cloud base height (a measure of moisture) and lightning flash counts show values in the order as Indian land 〉 Indian seas 〉 IGP. Geographic asymmetry of Indian land, IGP and Indian seas drive the continental and sea surface–atmosphere interactive processes that corroborate: (1) asymmetric synoptic scale delivery of moisture to Indian land and IGP from Indian seas revises the Bowen ratio, cloud base height and lightning activity, (2) increase in lightning activity with the total heat flux over Indian land and (3) enhance the lightning activity with the cloud base height/liquid condensation level.

Description: ABSTRACT Interpolating soil moisture at the regional scale (10 4 –10 7  km 2 ) is challenging because in situ observations tend to be sparse, and hydrometeorological conditions and soil characteristics have significant spatial variability. This study is the first to apply the reduced optimal interpolation (ROI) method to soil moisture. The ROI method uses both in situ and variable infiltration capacity (VIC) simulated-soil moisture to generate interpolated soil moisture surfaces in Oklahoma. The ROI method is based on an empirical orthogonal function (EOF) analysis that identifies the leading spatial modes of soil moisture variation based on the model simulation and then applies these EOFs using the temporal variations in the observed soil moisture. The interpolated soil moisture surfaces generated using ROI are compared with Cokriging, which also uses VIC simulations as a secondary input, and the inverse distance weighting (IDW) approach. The accuracy of all three interpolation methods are evaluated using soil moisture measurements from 65 stations. The ROI method is significantly more accurate than IDW and it also outperforms Cokriging. We demonstrate that ROI can be used to accurately depict the spatial patterns of soil moisture at the local and regional level.

Description: ABSTRACT In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central-eastern Europe. Several major heat episodes occurred from the end of June until mid-September. We provide an ad-hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901–2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east. During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central-) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003.

Description: ABSTRACT The impacts of El Niño (EN) on the rainfall over South America are investigated considering three EN types differing in the locations of the maximum sea surface temperature (SST) anomalies in the equatorial Pacific: the Central-Pacific (CP), Eastern-Pacific (EP) and the Mixed (MIX) types. The largest positive (SST) anomalies for the EP and CP types occur, respectively, in the eastern and central sectors of the tropical Pacific during all seasons. The SST anomaly pattern for the MIX-EN resembles that of the EP–EN during its onset stage, and of the CP–EN during its mature and demise stages. The different SST anomaly patterns affect the large-scale (Walker circulation and the tropospheric Rossby-wave trains) and local (South American low-level jet – SALLJ) atmospheric circulation patterns in different ways and lead to distinct precipitation anomaly patterns over South America. Variations in the position and longitudinal extension of the downward motions of the EN-related eastward-displaced Walker circulation explain the differences in the dryness over equatorial South America. For the CP–EN, a double Walker cell defines a more zonal configuration of the equatorial dryness over South America during the first three analysed seasons. This feature is not noted for the other two EN types. The Rossby-wave train pattern path depends on the EN types and seasons. In consequence, the associated local atmospheric circulation patterns depend also on the season and EN types. In all seasons, an intense SALLJ for the EP EN contrasts with weak or inexistence SALLJ for the other two EN types. Thus, a wetter condition over southeastern South America, southern and eastern Brazil occurs for the EP EN in relation to the other EN types. The results shown here, in particular considering the MIX EN type, have not been discussed before and might be useful mainly for climate monitoring purposes.

Description: ABSTRACT The relationship between interannual variability of Zimbabwe rainfall and atmosphere–ocean interaction processes is established using high-resolution rainfall station datasets. Empirical orthogonal function (EOF) analysis is used to extract the spatiotemporal modes that explain most of the variations in the rainfall pattern. Results suggest strong homogeneity in the rainfall pattern that is dominantly described by EOF mode 1. The correlation analysis of mode 1 with sea surface temperatures (SSTs) supports the assumption that El Niño Southern Oscillation (ENSO) has a significant influence on Zimbabwe summer rainfall. Significant correlations exist between rainfall and SSTs over large regions of the tropical Indian and Pacific Oceans. The seasonal response of rainfall to the southern annular mode is reflected in both modes 1 and 2. Mode 1 suggests homogeneity in rainfall variations within the country and mode 2 describes the north–south rainfall fluctuations in the country. Although the magnitudes of their loadings are small, modes 3 and 4 extracted distinct rainfall regions within the country. This could be attributed to the use of more reliable, higher resolution rainfall data. These findings will assist to bring profound improvements to seasonal rainfall forecasting techniques around the country.

Description: ABSTRACT Precipitation in the Tibetan Plateau (TP) reaches its peak in summer. The seasonal projection skill of a statistical downscaling model (SDM) for summer precipitation in the TP was compared with that of direct model output. The SDM, which is based on canonical correlation analysis (CCA), significantly increased the projection skill. The CCA reveals the flow patterns behind the seasonal projection skill of summer precipitation in the TP between 1961 and 2012 and quantifies its relative contributions. East Asia 500 hPa geopotential height (ZG500), tropical Indian Ocean sea surface temperature (SST) and east Asia 850 hPa meridional water vapour flux (MWVF850), obtained from the Max Planck Institute Earth System Model, low-resolution (MPI-ESM-LR) simulations for phase 5 of the Coupled Model Intercomparison Project under the representative concentration pathway (RCP) 2.6, RCP4.5 and RCP8.5 scenarios are considered as potential predictors. The SDMs are established in 1961–2005, validated in 2006–2012 and applied in 2013–2100. The ensemble canonical correlation (ECC) is also applied to improve projection skill. The following results are obtained: (1) The SDM projection skill for each predictor is higher than that of the MPI-ESM-LR climate model, and ECC performs even better. (2) Spatial correlation patterns of different predictors with influence on the TP are well recognized by CCA. The high relevance of ZG500 can be explained by the thermal adaptation theory, that of SST exhibits a canonical Indian Ocean Dipole mode, and MWVF850 shows a simple water vapour link. (3) The amount of summer precipitation in the TP will slightly decrease under RCP2.6 by −3.4 mm decade −1 , whereas RCP4.5 and RCP8.5 reveal an increase by 2.4 and 18.4 mm decade −1 , respectively.

Description: ABSTRACT The infrastructure design is primarily based on rainfall intensity–duration–frequency (IDF) curves, and the existing IDF curves are based on the concept of stationary extreme value theory (EVT) (i.e. the occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. Based on recent developments in the EVT, recent studies proposed a method for developing non-stationary rainfall IDF curve by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. Upon detecting a significant trend in the extreme rainfall series, directly applying the linear trend to develop non-stationary IDF curves may increase the bias of the non-stationary model. Hence, it is important to develop non-stationary GEV model which has less bias than the stationary model by modelling nonlinear trend in the series. In this study, we try to develop non-stationary GEV models with less bias by modelling nonlinear trend in the series using multi-objective genetic algorithm (MOGA). In addition, the proposed GEV model is compared with the stationary GEV model and the linear trend-based non-stationary GEV model. Furthermore, the Wilmington city and the Hyderabad city non-stationary IDF curves are developed and compared with stationary IDF curves. From the study results, it is observed that the proposed MOGA-based method is able to build the good quality and less bias non-stationary GEV models by modelling nonlinear trend in the series. In addition, it is also observed that the usage of linear trend for modelling non-stationarity in the time series sometimes increase the bias of non-stationary model.

Description: ABSTRACT Heatwaves have been linked to increased rates of human mortality and morbidity. Given these adverse health impacts, it is crucial to improve our understanding of future changes in these extreme events to inform health impacts studies and adaptation planning. While this information would be most beneficial at a local scale, Global Climate Models provide projections on much coarser resolutions. Regional Climate Models, such as those used in the New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project, provide simulations at a finer scale more appropriate for regional assessments. This study uses NARCliM output to investigate the ability of a Regional Climate Model ensemble to represent heatwave characteristics through the Excess Heat Factor, an index that includes factors that are known to be important to the heat-health relationship. Both uncorrected and bias-corrected model output is evaluated against observationally-derived heatwave characteristics for the period 1990–2009. The effect of bias-correction on future changes in heatwave characteristics is also assessed. Overall, the simulations provided a good representation of the recent climate and bias-correction did not greatly change simulated heatwave characteristics. Some regions were more affected by bias-correction than others, with bias-correction being most beneficial for coastal regions. We emphasise that these results may not apply to all indices measuring extreme heat, and demonstrate that results for an index based on a fixed absolute temperature threshold are substantially affected when bias-correction is applied. While supporting bias-correction, this study demonstrates that it is not necessarily required when evaluating a relative measure such as the Excess Heat Factor.

Description: ABSTRACT Developing high-quality long-term data sets at uniform space–time resolution is essential for improved climate studies. This article processes the outputs from two global and regional climate models, the Community Climate System Model (CCSM3) and the Regional Climate Model driven by the Hadley Centre Coupled Model (RegCM3). The results are bias-corrected time series of atmospheric variables corresponding to Intergovernmental Panel on Climate Change (IPCC's) historical (20C3M) and future (A2) climate scenarios over the Amazon Basin. We use a series of simple but effective interpolation approaches to produce hourly climate data sets at 1° by 1° grid cells. A quantile-based mapping approach is used to reduce the biases of temperature and precipitation in CCSM3 and RegCM3. Adjustments are also made on specific humidity and downwelling longwave radiation to avoid inconsistency between those variables and bias-corrected temperature values. We also interpolated an already bias-corrected Parallel Climate Model data set (PCM1) from 3-hourly to the hourly resolution. The final climate data sets can be used as forcing of ecosystem and hydrologic models to study climate changes and impact assessments over the Amazon Basin.